Introduction to Natural Language Processing

Semester B, 2022

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 (but unlikely to).

Course Requirements



Online Discussion Forums

Managed via Moodle


To be announced on Moodle.

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)

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

  3. Morphology, Parts of speech, and Tagging with HMMs slides

  4. Sequence Segmentation and discriminative tagging. slides

  5. Syntax, Grammars, Constituent slides || Dependency Syntax slides

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

  7. Distributional Similarity. slides

  8. More Distributional Similarity (embeddings). slides

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

  10. Representing Semantic Relationships / semantic roles slides

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

  12. Unsupervised Learning and LDA. slides