Introduction to Natural Language Processing

Semester A, 2020-2021

Instructors: Prof. Reut Tsarfaty, Prof. Yoav Goldberg and Prof. Ido Dagan
Emails: reut.tsarfaty/; yogo/; dagan/
Offices: Building 216
Office Hours: By email appointment

This week's class

Zoom Link (NOTE: this may change between weeks.)

Course Requirements



Online Discussion Forums

Managed via Piazza


  1. Assignment 1, Original deadline: Nov 17, Midnight. Updated deadline: Nov 19, Midnight.

  2. Assignment 2, deadline Dec 1, Midnight.

  3. Assignment 3, deadline Dec 22, Midgnight.

  4. Assignment 4, deadline Jan 15, Midnight.

Machine Learning Reading Material

Students who did not yet take Machine Learning, are encouraged to read the first 3 chapters of the following Book. You are encouraged to read chapters 4 and 5 also (as well as the rest of the book, but this is not needed for our class).


  1. Intro to Natural Language Processing, and discussion of sentence-boundary detection problem. Intro (Ido) || Intro (Reut) || Intro (Yoav) || [video]

  2. Classification (slides) || PP-attachment and simple probabilistic modeling (slides) || PP attachment data python example .html .ipynb
    || [video]

  3. Morphology, Parts of speech, and Tagging with HMMs slides || [video]

  4. Sequence Segmentation and discriminative tagging. slides || video

  5. Syntax, Grammars, Constituents slides || Dependency Syntax slides || video

  6. Parsing Algorithms. [phrases slides] [dependencies slides] || Video

  7. Distributional Similarity. slides || Video 1 || Video 2

  8. More Distributional Similarity (embeddings). slides || Video 1 || Video 2

  9. Contextualized embeddings. [slides] || Relation Extraction. [slides] || Video

  10. Representing Semantic Relationships / semantic roles slides || Video 1|| Video 2|| Video 3

  11. Coreference Resolution. slides 1 || slides 2. Annotation. Slides || Video

  12. Unsupervised Learning and LDA. slides || Video

  13. Biases in Text, Ethics. main slides, "making a racist AI" .html,.ipynb, Text is predictive of demographics slides (Yanai), Bias In Text slides, Ethics slides (Yulia) || Video

  14. About the exam, an NLP and Text Mining System. slides || Video