![Natural Language Processing Magdalena Wolska](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-organization/unit-en-nlp-organization-1.png)
![Contents I. Introduction](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-organization/unit-en-nlp-organization-2.png)
![Objectives](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-organization/unit-en-nlp-organization-3.png)
![Related Fields 1. Linguistics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-organization/unit-en-nlp-organization-4.png)
![Literature Natural Language Processing:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-organization/unit-en-nlp-organization-5.png)
![Literature Top-tier natural language processing conferences:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-organization/unit-en-nlp-organization-6.png)
![Literature Other relevant natural language processing conferences:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-organization/unit-en-nlp-organization-7.png)
![Software Annotation Software:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-organization/unit-en-nlp-organization-8.png)
![Software Algorithm Collections:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-organization/unit-en-nlp-organization-9.png)
![Chapter NLP:I I. Introduction](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-1.png)
![Goals of Language Technology 1. Aid humans in writing.](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-2.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-3.png)
![Chapter NLP:I I. Introduction](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-4.png)
![Examples of NLP Systems Writing Aid: Spelling and Grammar Checking](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-5.png)
![Examples of NLP Systems Writing Aid: Spelling and Grammar Checking](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-6.png)
![Examples of NLP Systems Writing Aid: Spelling and Grammar Checking](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-7.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-8.png)
![Examples of NLP Systems Question Answering: IBM Watson at Jeopardy](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-9.png)
![Examples of NLP Systems Question Answering: IBM Watson at Jeopardy](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-10.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-11.png)
![Examples of NLP Systems Question Answering: IBM Watson at Jeopardy](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-12.png)
![Examples of NLP Systems Question Answering: IBM Watson at Jeopardy](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-13.png)
![Examples of NLP Systems Question Answering: IBM Watson at Jeopardy](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-14.png)
![Examples of NLP Systems Question Answering: IBM Watson at Jeopardy](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-15.png)
![Examples of NLP Systems Question Answering: Jeopardy Revisited](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-16.png)
![Examples of NLP Systems Question Answering: Jeopardy Revisited](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-17.png)
![Chapter NLP:I I. Introduction](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-18.png)
![NLP Problems State of Affairs: Mostly Solved](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-19.png)
![NLP Problems State of Affairs: Mostly Solved](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-20.png)
![NLP Problems State of Affairs: Making Good Progress](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-21.png)
![NLP Problems State of Affairs: Making Good Progress](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-22.png)
![NLP Problems State of Affairs: Making Good Progress](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-23.png)
![NLP Problems State of Affairs: Still Challenging](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-24.png)
![NLP Problems State of Affairs: Still Challenging](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-25.png)
![NLP Problems State of Affairs: Still Challenging](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-26.png)
![NLP Problems State of Affairs: Still Challenging](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-27.png)
![NLP Problems State of Affairs: Still Challenging](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-28.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-29.png)
![Chapter NLP:I I. Introduction](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-30.png)
![Challenges for NLP Systems Why is NLP hard?](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-31.png)
![Challenges for NLP Systems Why is NLP hard?](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-32.png)
![Challenges for NLP Systems Why is NLP hard?](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-33.png)
![Challenges for NLP Systems Why is NLP hard?](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-34.png)
![Challenges for NLP Systems Why is NLP hard?](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-35.png)
![Challenges for NLP Systems Why is NLP hard?](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-36.png)
![Challenges for NLP Systems Why is NLP hard?](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-37.png)
![Challenges for NLP Systems Why is NLP hard?](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-38.png)
![Challenges for NLP Systems Why is NLP hard?](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-39.png)
![Challenges for NLP Systems Why is NLP hard?](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-40.png)
![Challenges for NLP Systems Why is NLP hard?](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-41.png)
![Challenges for NLP Systems Why is NLP hard?](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-nlp-introduction/unit-en-nlp-introduction-42.png)
![Chapter NLP:II II. Corpus Linguistics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-1.png)
![Empirical Research 1. Quantitative research based on numbers and statistics.](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-2.png)
![Empirical Research 1. Quantitative research based on numbers and statistics.](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-3.png)
![Empirical Research 1. Quantitative research based on numbers and statistics.](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-4.png)
![Empirical Research Research Questions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-5.png)
![Empirical Research Research Questions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-6.png)
![Empirical Research Research Questions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-7.png)
![Empirical Research Empirical Research in NLP](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-8.png)
![Empirical Research Empirical Research in NLP](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-9.png)
![Empirical Research Evaluation Measures](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-10.png)
![Empirical Research Effectiveness](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-11.png)
![Empirical Research Classification Effectiveness: Instance Types](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-12.png)
![Empirical Research Classification Effectiveness: Evaluation based on the Instance Types](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-13.png)
![Empirical Research Classification Effectiveness: Accuracy](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-14.png)
![Empirical Research Classification Effectiveness: Limitations of Accuracy](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-15.png)
![Empirical Research Classification Effectiveness: Precision and Recall](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-16.png)
![Empirical Research Classification Effectiveness: Precision and Recall Implications](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-17.png)
![Empirical Research Classification Effectiveness: Interplay between Precision and Recall](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-18.png)
![Empirical Research Classification Effectiveness: F1-Score](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-19.png)
![Empirical Research Classification Effectiveness: F1-Score Generalization](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-20.png)
![Empirical Research Classification Effectiveness: F1-Score Issue in Tasks with Boundary Detection](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-21.png)
![Empirical Research Classification Effectiveness: Other F1-Score Issues](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-22.png)
![Empirical Research Classification Effectiveness: Micro- and Macro-Averaging](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-23.png)
![Empirical Research Classification Effectiveness: Confusion Matrix for Micro- and Macro-Averaging](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-24.png)
![Empirical Research Classification Effectiveness: Computing Micro- and Macro-Averages](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-25.png)
![Empirical Research Regression Effectiveness](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-26.png)
![Empirical Research Regression Effectiveness: Types of Regression Errors](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-27.png)
![Empirical Research Regression Effectiveness: Computation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-28.png)
![Empirical Research Other Measures](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-29.png)
![Empirical Research Experiments](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-30.png)
![Empirical Research Datasets](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-31.png)
![Empirical Research Types of Evaluation: Training, Validation, and Test Set](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-32.png)
![Empirical Research Types of Evaluation: Cross-Validation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-33.png)
![Empirical Research Types of Evaluation: Variations](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-34.png)
![Empirical Research Training Data](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-35.png)
![Empirical Research Comparison](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-36.png)
![Empirical Research Comparison: Upper and Lower Bounds](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-37.png)
![Empirical Research Comparison: Types of Baselines](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-38.png)
![Empirical Research Comparison: Exemplary Baselines](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-39.png)
![Empirical Research Comparison: Implications](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-40.png)
![Chapter NLP:II II. Corpus Linguistics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-41.png)
![Hypothesis Testing Statistics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-42.png)
![Hypothesis Testing Statistics: Variables and Scales](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-43.png)
![Hypothesis Testing Descriptive Statistics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-44.png)
![Hypothesis Testing Descriptive Statistics: Central Tendency and its Disperson](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-45.png)
![Hypothesis Testing Descriptive Statistics: Normal Distribution](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-46.png)
![Hypothesis Testing Descriptive Statistics: Standard Scores](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-47.png)
![Hypothesis Testing Inferential Statistics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-48.png)
![Hypothesis Testing Inferential Statistics: Hypotheses](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-49.png)
![Hypothesis Testing Four Steps of Hypothesis Testing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-50.png)
![Hypothesis Testing Effect Size](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-51.png)
![Hypothesis Testing What Test to Choose](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-52.png)
![Hypothesis Testing Assumptions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-53.png)
![Hypothesis Testing The Student’s t-Test](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-54.png)
![Hypothesis Testing One-Sample t-Test](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-55.png)
![Hypothesis Testing Dependent t-Test (aka paired-sample test)](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-56.png)
![Hypothesis Testing Independent t-Test](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-57.png)
![Hypothesis Testing The Student’s t-Test: What to do with the t-Score?](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-58.png)
![Hypothesis Testing Example: One-Tailed One-Sample t-Test](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-empirical-research/unit-en-empirical-research-59.png)
![Chapter NLP:II II. Corpus Linguistics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-1.png)
![Text Corpora Corpus Linguistics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-2.png)
![Text Corpora Corpus Linguistics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-3.png)
![Text Corpora Definition 1 (Text Corpus [Butler 2004])](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-4.png)
![Text Corpora Text as Data](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-5.png)
![Text Corpora Text as Data](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-6.png)
![Text Corpora Metadata](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-7.png)
![Text Corpora Research in Language Use](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-8.png)
![Text Corpora Research in Language Use](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-9.png)
![Text Corpora Vocabulary Growth: Heaps’ Law](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-10.png)
![Text Corpora Vocabulary Growth: Heaps’ Law](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-11.png)
![Text Corpora Term Frequency: Zipf’s Law](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-12.png)
![Text Corpora Term Frequency: Zipf’s Law](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-13.png)
![Text Corpora Term Frequency: Zipf’s Law](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-14.png)
![Text Corpora Term Frequency: Zipf’s Law](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-15.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-16.png)
![Text Corpora Term Frequency: Zipf’s Law](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-17.png)
![Text Corpora Term Frequency: Zipf’s Law](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-18.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-19.png)
![Text Corpora Term Frequency: Zipf’s Law](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-20.png)
![Text Corpora Term Frequency: Zipf’s Law](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-21.png)
![Text Corpora n-grams](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-22.png)
![Text Corpora n-grams](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-23.png)
![Text Corpora n-grams](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-24.png)
![Text Corpora n-gram Corpora](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-25.png)
![Text Corpora n-gram Corpora](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-26.png)
![Chapter NLP:II II. Corpus Linguistics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-27.png)
![Data Acquisition Data Sources](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-28.png)
![Data Acquisition Newspapers](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-29.png)
![Data Acquisition Blogs and Forums](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-30.png)
![Data Acquisition Social network](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-31.png)
![Data Acquisition Other Sources](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-32.png)
![Data Acquisition On Representativeness](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-33.png)
![Data Acquisition Representative Data versus Balanced Data](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-corpora/unit-en-corpora-34.png)
![Chapter NLP:II II. Corpus Linguistics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-1.png)
![Data Annotation Definition 1 (Annotation)](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-2.png)
![Data Annotation Sources of Annotations](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-3.png)
![Data Annotation Automatic Annotation: Sources](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-4.png)
![Data Annotation Manual Annotation: Sources](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-5.png)
![Data Annotation Manual Annotations: Software](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-6.png)
![Data Annotation Crowdsourcing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-7.png)
![Data Annotation Crowdsourcing: Platforms](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-8.png)
![Data Annotation Crowdsourcing: Issues](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-9.png)
![Data Annotation Crowdsourcing: Gamification](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-10.png)
![Data Annotation Crowdsourcing: Gamification](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-11.png)
![Data Annotation Annotation Tasks](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-12.png)
![Data Annotation Annotation Tasks](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-13.png)
![Data Annotation Annotation Schemes](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-14.png)
![Data Annotation Annotation Schemes: Guidelines](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-15.png)
![Data Annotation Annotation Schemes: Disagreement](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-16.png)
![Data Annotation Annotation Schemes: Disagreement](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-17.png)
![Data Annotation Annotation Schemes: Disagreement](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-18.png)
![Data Annotation Annotation Schemes: Disagreement](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-19.png)
![Data Annotation Annotation Schemes: Disagreement](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-20.png)
![Data Annotation Annotator Agreement: Observed Agreement](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-21.png)
![Data Annotation Annotator Agreement: Observed Agreement](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-22.png)
![Data Annotation Annotator Agreement: Observed Agreement](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-23.png)
![Data Annotation Annotator Agreement: Cohen’s κ](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-24.png)
![Data Annotation Annotator Agreement: Cohen’s κ](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-25.png)
![Data Annotation Annotator Agreement: Fleiss’s κ](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-26.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-27.png)
![Data Annotation Non-technical Aspects](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-annotation/unit-en-annotation-28.png)
![Chapter NLP:III III. Text Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-1.png)
![Text Preprocessing Overview](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-2.png)
![Text Preprocessing Overview](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-3.png)
![Text Preprocessing Overview](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-4.png)
![Text Preprocessing Overview](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-5.png)
![Text Preprocessing Preprocessing Pipeline](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-6.png)
![Text Preprocessing Preprocessing Pipeline](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-7.png)
![Text Preprocessing Preprocessing Pipeline](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-8.png)
![Text Preprocessing Preprocessing Pipeline](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-9.png)
![Remarks: Annotation is skipped when the annotations are not needed for further processing.](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-10.png)
![Text Preprocessing Token Normalization](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-11.png)
![Text Preprocessing Token Normalization: Regular Expressions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-12.png)
![Text Preprocessing Token Normalization: Regular Expressions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-13.png)
![Text Preprocessing Token Normalization: Regular Expressions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-14.png)
![Text Preprocessing Token Normalization: Regular Expressions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-15.png)
![Text Preprocessing Token Normalization: Regular Expressions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-16.png)
![Text Preprocessing Token Normalization: Regular Expressions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-17.png)
![Text Preprocessing Token Normalization: Regular Expressions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-18.png)
![Text Preprocessing Token Normalization: Regular Expressions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-19.png)
![Text Preprocessing Token Normalization: Regular Expressions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-20.png)
![Text Preprocessing Token Normalization: Regular Expressions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-21.png)
![Text Preprocessing Token Normalization: Regular Expressions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-22.png)
![Text Preprocessing Token Normalization: Regular Expressions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-23.png)
![Text Preprocessing Token Normalization: Regular Expressions Summary](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-24.png)
![Text Preprocessing Tokenization](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-25.png)
![Text Preprocessing Tokenization: Special Cases](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-26.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-27.png)
![Text Preprocessing Tokenization: Approaches](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-28.png)
![Text Preprocessing Tokenization: Rule-based [Jurafsky and Martin, 2007] [Grefenstette, 1999]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-29.png)
![Text Preprocessing Tokenization: Rule-based [Jurafsky and Martin, 2007] [Grefenstette, 1999]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-30.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-31.png)
![Text Preprocessing Problems of Rule-based Tokenization](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-32.png)
![Text Preprocessing Tokenization: Byte-Pair Encoding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-33.png)
![Text Preprocessing Tokenization: Byte-Pair Encoding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-34.png)
![Text Preprocessing Tokenization: Byte-Pair Encoding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-35.png)
![Text Preprocessing Tokenization: Byte-Pair Encoding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-36.png)
![Text Preprocessing Tokenization: Byte-Pair Encoding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-37.png)
![Text Preprocessing Tokenization: Byte-Pair Encoding Rule Finding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-38.png)
![Text Preprocessing Tokenization: Byte-Pair Encoding Rule Finding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-39.png)
![Text Preprocessing Tokenization: Byte-Pair Encoding Rule Finding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-40.png)
![Text Preprocessing Tokenization: Byte-Pair Encoding Rule Finding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-41.png)
![Text Preprocessing Tokenization: Byte-Pair Encoding Rule Finding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-42.png)
![Text Preprocessing Tokenization: Byte-Pair Encoding Rule Finding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-43.png)
![Text Preprocessing Tokenization: Byte-Pair Encoding Rule Finding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-44.png)
![Text Preprocessing Tokenization: Byte-Pair Encoding Rule Finding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-45.png)
![Text Preprocessing Tokenization: Byte-Pair Encoding Rule Finding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-46.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-47.png)
![Text Preprocessing Tokenization: Token Removal](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-48.png)
![Text Preprocessing Tokenization: Token Removal](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-49.png)
![Text Preprocessing Tokenization: Token Removal](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-preprocessing/unit-en-text-preprocessing-50.png)
![Chapter NLP:III III. Text Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-1.png)
![Text Representation Models of Representation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-2.png)
![Text Representation Token Representations](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-3.png)
![Text Representation Document Representation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-4.png)
![Text Representation Document Representation: Bag of Words Metaphor](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-5.png)
![Text Representation Document Representation: Vector Space Model [Salton et. al. 1975]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-6.png)
![Text Representation Document Representation: Vector Space Model [Salton et. al. 1975]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-7.png)
![Text Representation Document Representation: Vector Space Model [Salton et. al. 1975]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-8.png)
![Remarks: DTMs can become very large and very sparse (approx. 95% of elements are zero).](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-9.png)
![Text Representation Term Weighting: tf ·idf](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-10.png)
![Text Representation Term Weighting: tf ·idf](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-11.png)
![Text Representation Term Weighting: tf ·idf](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-12.png)
![Text Representation Term Weighting: tf ·idf](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-13.png)
![Text Representation Term Weighting: tf ·idf](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-14.png)
![Text Representation Term Weighting: tf ·idf Example](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-15.png)
![Text Representation Term Weighting: tf ·idf Example](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-16.png)
![Text Representation Term Weighting: tf ·idf Example](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-17.png)
![Text Representation Term Weighting: tf ·idf Example](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-18.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-19.png)
![Text Representation Vocabulary Pruning](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-20.png)
![Text Representation Distributional Representations of Words](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-21.png)
![Remarks: There are two other relevant hypotheses for distributional semantics.](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-22.png)
![Text Representation Distributional Representations of Words](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-23.png)
![Text Representation Co-occurrence Vectors](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-24.png)
![Text Representation Co-occurrence Vectors](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-25.png)
![Remarks: Principal components are linearly orthogonal vectors and differ by direction and the abount of](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-26.png)
![Text Representation Word2Vec](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-27.png)
![Text Representation Word2Vec](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-28.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-29.png)
![Text Representation Properties of Word Vectors](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-30.png)
![Text Representation Sentence Embeddings](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-31.png)
![Text Representation Sentence Embeddings](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-representation/unit-en-text-representation-32.png)
![Chapter NLP:III III. Text Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-1.png)
![Text Similarity Text can be similar in different ways:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-2.png)
![Text Similarity Text can be similar in different ways:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-3.png)
![Text Similarity Similarity Measures](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-4.png)
![Text Similarity String-based Similarity: Hamming Distance](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-5.png)
![Text Similarity String-based Similarity: Levenshtein Distance](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-6.png)
![Text Similarity String-based Similarity](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-7.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-8.png)
![Text Similarity Resource-based Similarity: Thesaurus relations](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-9.png)
![Text Similarity Resource-based Similarity](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-10.png)
![Text Similarity Vector Distance](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-11.png)
![Text Similarity Vector Distance](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-12.png)
![Text Similarity Vector Similarity: Cosine Similarity](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-13.png)
![Text Similarity Vector Similarity: Cosine Similarity](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-14.png)
![Text Similarity Vector Similarity: Jaccard Similarity](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-15.png)
![Text Similarity Vector Similarity: Divergence](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-16.png)
![Text Similarity Vector Similarity](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-17.png)
![Remarks: Count vectors can be transformed into probability distributions (cf. Probability Mass](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-18.png)
![Similarity Measures Word Vector Similarity: Sentence Embeddings](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-19.png)
![Similarity Measures Word Vector Similarity: Sentence Embeddings](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-20.png)
![Similarity Measures Word Vector Similarity: Word Mover Distance](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-21.png)
![Similarity Measures Word Vector Similarity: Word Mover Distance](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-22.png)
![Similarity Measures Word Vector Similarity: Word Mover Distance](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-23.png)
![Text Similarity Word Vector Similarity](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-similarity/unit-en-text-similarity-24.png)
![Chapter NLP:III III. Text Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-1.png)
![Text Classification Text Classification Problems](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-2.png)
![Text Classification Text Classification Problems](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-3.png)
![Text Classification Text Classification Problems](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-4.png)
![Text Classification Text Classification Problems](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-5.png)
![Text Classification Text Classification Problems](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-6.png)
![Text Classification Text Classification Problems](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-7.png)
![Text Classification Classification Tasks](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-8.png)
![Text Classification Classification Tasks](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-9.png)
![Text Classification Classification Tasks](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-10.png)
![Remarks: Classification and Regression in NLP](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-11.png)
![Text Classification Classification Tasks: Classes C](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-12.png)
![Text Classification Classification Tasks: Objects O](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-13.png)
![Remarks: Many (non-neural) classification algorithms work for |C| = 2 classes only. Multi-class and](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-14.png)
![Text Classification Feature space X](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-15.png)
![Text Classification Feature Engineering](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-16.png)
![Text Classification Content Features](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-17.png)
![Text Classification Linguistic Structure Features](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-18.png)
![Text Classification Task-specific features (a selection)](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-19.png)
![Text Classification Feature Engineering](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-20.png)
![Text Classification Representation Learning](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-21.png)
![Text Classification Representation Learning](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-22.png)
![Text Classification Feature Space Size](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-23.png)
![Text Classification Feature Space Size](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-24.png)
![Text Classification Common Classification Algorithms](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-25.png)
![Text Classification Evaluation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-26.png)
![Text Classification Dataset Preparation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-27.png)
![Text Classification Dataset Preparation: Negative Instances](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-28.png)
![Text Classification Dataset Preparation: Negative Instances](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-29.png)
![Text Classification Dataset Preparation: Mapping of Target Variable Values](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-30.png)
![Text Classification Dataset Preparation: Balancing Datasets](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-31.png)
![Text Classification Dataset Preparation: Balancing Datasets](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-32.png)
![Text Classification Dataset Preparation: Balancing Datasets](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-33.png)
![Text Classification Dataset Preparation: Balancing Datasets](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-34.png)
![Dataset Preparations Undersampling vs. Oversampling](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-classification/unit-en-text-classification-35.png)
![Chapter NLP:IV IV. Text Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-1.png)
![Language Modeling Definition 1 (Language Model)](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-2.png)
![Language Modeling Definition 1 (Language Model)](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-3.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-4.png)
![Language Modeling Applications](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-5.png)
![Language Modeling Language Model Estimation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-6.png)
![Language Modeling Language Model Estimation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-7.png)
![Language Modeling Language Model Estimation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-8.png)
![Language Modeling Language Model Estimation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-9.png)
![Language Modeling Language Model Estimation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-10.png)
![q](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-11.png)
![Language Modeling Language Model Estimation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-12.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-13.png)
![Language Modeling Bi-gram Model](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-14.png)
![Language Modeling Bi-gram Model](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-15.png)
![Language Modeling Bi-gram Model](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-16.png)
![Language Modeling Bi-gram Model](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-17.png)
![Language Modeling Bi-gram Model](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-18.png)
![Language Modeling The N-gram Model](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-19.png)
![Language Modeling The N-gram Model](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-20.png)
![Language Modeling The N-gram Model](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-21.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-22.png)
![Language Modeling Improving the N-gram Model: Smoothing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-23.png)
![Language Modeling Denominator Smoothing: Stupid Backoff](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-24.png)
![Language Modeling Denominator Smoothing: Linear Interpolation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-25.png)
![Language Modeling Denominator Smoothing: Linear Interpolation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-26.png)
![Language Modeling Numerator Smoothing: Add-one (Laplace) smoothing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-27.png)
![Language Modeling Numerator Smoothing: Add-one (Laplace) smoothing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-28.png)
![Language Modeling Numerator Smoothing: Add-one (Laplace) smoothing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-29.png)
![Language Modeling Numerator Smoothing: Good-Turing smoothing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-30.png)
![Language Modeling Numerator Smoothing: Kneser-Ney Smoothing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-31.png)
![Language Modeling Numerator Smoothing: Kneser-Ney Smoothing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-32.png)
![Language Modeling Numerator Smoothing: Kneser-Ney Smoothing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-33.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-34.png)
![Language Modeling Conditional Language Modeling](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-35.png)
![Remarks: Conditional language models are the basis for large language models (LLMs).](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-language-modeling/unit-en-language-modeling-36.png)
![Chapter NLP:IV IV. Text Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-1.png)
![Large Language Models Neural Language Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-2.png)
![Large Language Models Neural Language Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-3.png)
![Large Language Models Neural Language Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-4.png)
![Large Language Models Neural Language Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-5.png)
![Large Language Models Neural Language Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-6.png)
![Large Language Models Neural Language Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-7.png)
![Remarks: RNN Notation: t incidates the timestep. The weight matrices wh for encoding and wo are the](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-8.png)
![Large Language Models Transformer Architecture Overview](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-9.png)
![Large Language Models Transformer Architecture Overview: Transformer Block](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-10.png)
![Large Language Models Transformer Architecture Overview: Transformer Block](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-11.png)
![Large Language Models Transformer Architecture Overview: Transformer Block](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-12.png)
![Large Language Models Transformer Architecture Overview: Transformer Block](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-13.png)
![Large Language Models Transformer Architecture Overview: Transformer Block](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-14.png)
![Large Language Models Transformer Architecture Overview: Self-attention](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-15.png)
![Large Language Models Transformer Architecture Overview: Self-attention](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-16.png)
![Large Language Models Transformer Architecture Overview: Self-attention](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-17.png)
![Large Language Models Transformer Architecture Overview: Multi-headed Self-attention](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-18.png)
![Large Language Models Transformer Architecture Overview: Multi-headed Self-attention](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-19.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-20.png)
![Large Language Models Transformer Language Models: Types](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-21.png)
![Large Language Models Pre-training and Fine-tuning](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-22.png)
![Large Language Models Pre-training and Fine-tuning](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-23.png)
![Large Language Models Pre-training and Fine-tuning](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-24.png)
![Large Language Models Autoregressive Large Language Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-25.png)
![Large Language Models Autoregressive Large Language Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-26.png)
![Large Language Models LLM Fine-tuning: Instruction Tuning](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-27.png)
![Large Language Models Bidirectional Language Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-28.png)
![Large Language Models Bidirectional Language Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-29.png)
![Large Language Models Bidirectional Language Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-30.png)
![Large Language Models BERT Fine-tuning](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-31.png)
![Large Language Models Encoder-Decoder Language Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-large-language-models/unit-en-large-language-models-32.png)
![Chapter NLP:IV IV. Text Models](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-1.png)
![Text Generation Autoregressive language models generate text by iteratively](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-2.png)
![Text Generation Decoding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-3.png)
![Text Generation Decoding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-4.png)
![Text Generation Decoding](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-5.png)
![Text Generation Scoring: Temperature](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-6.png)
![Text Generation Scoring: Temperature](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-7.png)
![Text Generation Scoring: Temperature](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-8.png)
![Text Generation Scoring: Temperature](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-9.png)
![Text Generation Scoring: Top-k Sampling](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-10.png)
![Text Generation Scoring: Top-k Sampling](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-11.png)
![Text Generation Scoring: Top-k Sampling](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-12.png)
![Text Generation Scoring: Nucleus (Top-p) Sampling](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-13.png)
![Text Generation Scoring: Nucleus (Top-p) Sampling](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-14.png)
![Text Generation Strategy: Contrastive Search](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-15.png)
![Text Generation Strategy: Contrastive Search](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-16.png)
![Text Generation Strategy: Contrastive Search](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-17.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-18.png)
![Text Generation Strategy: Beam Search](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-19.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-text-generation/unit-en-text-generation-20.png)
![Chapter NLP:V V. Words](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-1.png)
![Morphology Overview [Hancox 1996]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-2.png)
![Morphology Overview [Hancox 1996]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-3.png)
![Morphology Overview [Hancox 1996]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-4.png)
![Morphology Overview [Hancox 1996]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-5.png)
![Morphology Stemming](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-6.png)
![Morphology Stemming: Principles [Frakes 1992]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-7.png)
![Morphology Stemming: Affix Elimination](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-8.png)
![Morphology Stemming: Porter Stemmer](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-9.png)
![Morphology Stemming: Porter Stemmer](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-10.png)
![Morphology Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-11.png)
![Morphology Stemming: Porter Stemmer](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-12.png)
![Morphology Stemming: Porter Stemmer](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-13.png)
![Morphology Stemming: Porter Stemmer](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-14.png)
![Morphology Stemming: Porter Stemmer](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-15.png)
![Morphology Stemming: Porter Stemmer](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-16.png)
![Morphology Stemming: Krovetz Stemmer](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-17.png)
![Morphology Stemming: Stemmer Comparison](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-18.png)
![Morphology Stemming: Stemmer Comparison](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-19.png)
![Morphology Stemming: Stemmer Comparison](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-20.png)
![Morphology Stemming: Character n-grams [McNamee et al. 2004] [McNamee et al. 2008]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-21.png)
![Morphology Stemming: Character n-grams [McNamee et al. 2004] [McNamee et al. 2008]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-22.png)
![Morphology Lemmatization](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-morphology/unit-en-morphology-23.png)
![Chapter NLP:V V. Words](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-1.png)
![Word Classes Definition](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-2.png)
![Word Classes Traditional grammar](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-3.png)
![Word Classes Traditional grammar: Example](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-4.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-5.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-6.png)
![Word Classes Tagsets](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-7.png)
![Word Classes Penn Treebank tagset [upenn]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-8.png)
![Word Classes Penn Treebank tagset [upenn]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-9.png)
![Word Classes Penn Treebank tagset [upenn]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-10.png)
![Word Classes Penn Treebank tagset [upenn]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-11.png)
![Word Classes Penn Treebank tagset [upenn]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-12.png)
![Word Classes Universal Dependencies tagset [UD]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-13.png)
![Word Classes Universal Dependencies tagset [UD]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-14.png)
![Word Classes Ambiguities](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-15.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-16.png)
![Word Classes Part-of-Speech Tagging](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-17.png)
![Word Classes Part-of-Speech Tagging](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-18.png)
![Word Classes Part-of-Speech Tagging: Maximum Likelihood Estimate](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-19.png)
![Word Classes Part-of-Speech Tagging: Brill Tagger [Brill 1992]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-20.png)
![Word Classes Part-of-Speech Tagging: Brill Tagger [Brill 1992]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-21.png)
![Word Classes Part-of-Speech Tagging: Brill Tagger [Brill 1994]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-22.png)
![Word Classes Part-of-Speech Tagging: Brill Tagger [Brill 1994]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-23.png)
![Word Classes Part-of-Speech Tagging: Token Classification](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-24.png)
![Word Classes Part-of-Speech Tagging: Token Classification](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-25.png)
![Word Classes Token Classification](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-26.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-27.png)
![Word Classes Part-of-Speech Tagging](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-28.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-word-classes/unit-en-word-classes-29.png)
![Chapter NLP:V V. Words](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-named-entities/unit-en-named-entities-1.png)
![Named Entities Entities](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-named-entities/unit-en-named-entities-2.png)
![Named Entities Named Entities](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-named-entities/unit-en-named-entities-3.png)
![Named Entities Named Entities](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-named-entities/unit-en-named-entities-4.png)
![Remarks: Named entity tagsets vary by corpus and use case:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-named-entities/unit-en-named-entities-5.png)
![Named Entities Named Entity Recognition](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-named-entities/unit-en-named-entities-6.png)
![Named Entities BIO Tagging](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-named-entities/unit-en-named-entities-7.png)
![Named Entities BIO Tagging](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-named-entities/unit-en-named-entities-8.png)
![Remarks: Two popular variations of BIO are IO and BIOES.](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-named-entities/unit-en-named-entities-9.png)
![Chapter NLP:VI VI. Syntax](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-grammar-formalisms/unit-en-grammar-formalisms-1.png)
![Grammar Formalisms Problem: Given a set of symbols, how do they incur meaning?](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-grammar-formalisms/unit-en-grammar-formalisms-2.png)
![Grammar Formalisms Problem: Given a set of symbols, how do they incur meaning?](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-grammar-formalisms/unit-en-grammar-formalisms-3.png)
![Grammar Formalisms Grammars](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-grammar-formalisms/unit-en-grammar-formalisms-4.png)
![Grammar Formalisms Grammars](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-grammar-formalisms/unit-en-grammar-formalisms-5.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-grammar-formalisms/unit-en-grammar-formalisms-6.png)
![Grammar Formalisms Syntax Structures](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-grammar-formalisms/unit-en-grammar-formalisms-7.png)
![Grammar Formalisms Syntax Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-grammar-formalisms/unit-en-grammar-formalisms-8.png)
![Grammar Formalisms Ambiguity](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-grammar-formalisms/unit-en-grammar-formalisms-9.png)
![Grammar Formalisms Ambiguity](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-grammar-formalisms/unit-en-grammar-formalisms-10.png)
![Grammar Formalisms Ambiguity](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-grammar-formalisms/unit-en-grammar-formalisms-11.png)
![Chapter NLP:VI VI. Syntax](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-1.png)
![Phrase Structure Grammars Formal Grammars](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-2.png)
![Phrase Structure Grammars Chomsky Hierarchy](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-3.png)
![Remarks: Context-sensitive grammars allow multiple symbols on the left side (but at least one](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-4.png)
![Phrase Structure Grammars Context-free grammars (CFG)](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-5.png)
![Phrase Structure Grammars Context-free grammars (CFG)](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-6.png)
![Phrase Structure Grammars Context-free grammars (CFG)](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-7.png)
![Phrase Structure Grammars Context-free grammars (CFG)](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-8.png)
![Phrase Structure Grammars Context-free grammars (CFG)](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-9.png)
![Phrase Structure Grammars CFG: Example Grammar](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-10.png)
![Phrase Structure Grammars CFG Construction: Treebanks](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-11.png)
![Phrase Structure Grammars Constituency Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-12.png)
![Phrase Structure Grammars CFG Modifications for Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-13.png)
![Phrase Structure Grammars Probabilistic CFG](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-14.png)
![Phrase Structure Grammars Probabilistic CFG](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-15.png)
![Phrase Structure Grammars Chomsky Normal Form](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-16.png)
![Phrase Structure Grammars Chomsky Normal Form](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-17.png)
![Phrase Structure Grammars Chomsky Normal Form](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-18.png)
![Phrase Structure Grammars CNF Transformation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-19.png)
![Phrase Structure Grammars CNF Transformation: Replace Empty Rules](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-20.png)
![Phrase Structure Grammars CNF Transformation: Replace Unary Rules (1)](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-21.png)
![Phrase Structure Grammars CNF Transformation: Replace Unary Rules (2)](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-22.png)
![Phrase Structure Grammars CNF Transformation: Replace Unary Rules (3-7)](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-23.png)
![Phrase Structure Grammars CNF Transformation: Split n-ary rules with n ≥ 3](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-24.png)
![Phrase Structure Grammars Chomsky Normal Form Transformation: Pseudocode](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-25.png)
![Remarks: The original algorithm presented by Chomsky has 5 steps: START, TERM, BIN, DEL, and](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-26.png)
![Phrase Structure Grammars Cocke-Kasami-Younger (CKY) Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-27.png)
![Parsing based on a PCFG Cocke-Kasami-Younger (CKY) Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-28.png)
![Parsing based on a PCFG Cocke-Kasami-Younger (CKY) Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-29.png)
![Parsing based on a PCFG Cocke-Kasami-Younger (CKY) Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-30.png)
![Parsing based on a PCFG Cocke-Kasami-Younger (CKY) Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-31.png)
![Parsing based on a PCFG Cocke-Kasami-Younger (CKY) Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-32.png)
![Remarks: The binarization from the CNF is crucial for cubic time.](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-33.png)
![Phrase Structure Grammars CKY Parsing: Pseudo Code 1/2](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-34.png)
![Parsing based on a PCFG CKY Parsing: Pseudo Code 1/2](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-35.png)
![Phrase Structure Grammars CKY Parsing: Pseudo Code 2/2](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-36.png)
![Phrase Structure Grammars CKY Parsing: Pseudo Code 2/2](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-37.png)
![Phrase Structure Grammars CKY Parsing: Pseudo Code 2/2](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-38.png)
![Phrase Structure Grammars CKY Parsing: Example](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-39.png)
![Phrase Structure Grammars CKY Parsing: Example](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-40.png)
![Phrase Structure Grammars CKY Parsing: Example](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-41.png)
![Phrase Structure Grammars CKY Parsing: Example](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-42.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-43.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-44.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-45.png)
![Phrase Structure Grammars Lexicalization](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-46.png)
![Phrase Structure Grammars Lexicalized PCFG parsing[Collins, 1999]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-47.png)
![Phrase Structure Grammars Unlexicalization[Klein and Manning, 2003]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-48.png)
![Phrase Structure Grammars Linearized parsing[Vinyals, Kaiser, et al., 2015]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-49.png)
![Remarks: Vinyals, Kaiser, et al. present linearaization as “Grammar as a Foreign Language”.](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-50.png)
![Phrase Structure Grammars Evaluation[Sekine and Collins, evalb]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-51.png)
![Phrase Structure Grammars Evaluation[Sekine and Collins, evalb]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-52.png)
![Phrase Structure Grammars Evaluation[Sekine and Collins, evalb]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-53.png)
![Remarks: Those evaluation measures were developed at the PARSEVAL Workshop in 1998 and are](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-54.png)
![Phrase Structure Grammars Evaluation: Comparison of Methods](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-phrase-structure-grammar/unit-en-phrase-structure-grammar-55.png)
![Chapter NLP:VI VI. Syntax](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-1.png)
![Dependency Grammars Definition](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-2.png)
![Dependency Grammars Properties of Dependencies](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-3.png)
![Remarks: Dependencies often approximate semantic relationships. Knowing the head-dependent](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-4.png)
![Dependency Grammars Dependency Treebanks: Universal Dependencies[UD, 2021]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-5.png)
![Dependency Grammars Universal Dependency Relations[de Marneffe et al., 2014]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-6.png)
![Dependency Grammars Universal Dependency Relations[de Marneffe et al., 2014]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-7.png)
![Dependency Grammars Universal Dependency Relations[de Marneffe et al., 2014]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-8.png)
![Dependency Grammars Transition-based parsing[Nivre, 2008]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-9.png)
![Dependency Grammars Transition-based parsing[Nivre, 2008]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-10.png)
![Dependency Grammars Transition-based parsing[Nivre, 2008]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-11.png)
![Dependency Grammars Arc-Standard Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-12.png)
![Dependency Grammars Arc-Standard Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-13.png)
![Dependency Grammars Arc-Standard Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-14.png)
![Dependency Grammars Arc-Standard Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-15.png)
![Dependency Grammars Arc-Standard Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-16.png)
![Dependency Grammars Arc-Standard Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-17.png)
![Dependency Grammars Arc-Standard Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-18.png)
![Dependency Grammars Arc-Standard Parsing: Oracles](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-19.png)
![Dependency Grammars Arc-Standard Parsing: Oracles](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-20.png)
![Dependency Grammars Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-21.png)
![Dependency Grammars Projectivity[McDonald et al., 2005]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-22.png)
![Dependency Grammars Graph-based Parsing](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-23.png)
![Dependency Grammars Evaluation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-24.png)
![Dependency Grammars Evaluation: Comparison of Methods](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-dependency-grammar/unit-en-dependency-grammar-25.png)
![Chapter NLP:VII VII. Semantics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-1.png)
![Semantic Structures Semantics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-2.png)
![Semantic Structures Semantics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-3.png)
![Remarks Semantics stems from the ancient Greek semantikos (relating to signs as in symptoms of a](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-4.png)
![Semantic Structures Lexical Semantics[OxfordRE Linguistics]](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-5.png)
![Semantic Structures Lexical Semantics: Word Senses](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-6.png)
![Semantic Structures Lexical Semantics: Lexical Relations (selection)](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-7.png)
![Semantic Structures Lexical Semantics: WordNet](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-8.png)
![Semantic Structures Lexical Semantics: WordNet](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-9.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-10.png)
![Semantic Structures Word Sense Disambiguation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-11.png)
![Semantic Structures Word Sense Disambiguation: Lesk](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-12.png)
![Semantic Structures Word Sense Disambiguation: Lesk](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-13.png)
![Semantic Structures Word Sense Disambiguation: Classification](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-14.png)
![Remarks:](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-15.png)
![Semantic Structures Lexical Substitution](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-16.png)
![Semantic Structures Multi-Word Expressions](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-17.png)
![Semantic Structures Limitations of Lexical Semantics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-18.png)
![Semantic Structures Compositional Semantics](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-19.png)
![Semantic Structures Compositional Semantics: Semantic Relations](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-20.png)
![Semantic Structures Compositional Semantics: Operators](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-21.png)
![Semantic Structures Compositional Semantics: Collocation](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-22.png)
![Remarks: A statistical approach to extract collocation from a corpus is cooccurrence significance on](https://downloads.webis.de/lecturenotes/natural-language-processing/unit-en-semantic-structures/unit-en-semantic-structures-23.png)
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