Course Description

This course covers algorithms for associating deep or elaborated linguistic structures with naturally occurring data, covering parsing, semantics, and discourse.

Days Time Location
Monday and Wednesday 1:00 - 2:20 PM DEN 258

Note: while lectures will be delivered live at the above time and location, they will also be recorded and posted to the course Canvas page.

Teaching Staff

Role Name Office Office Hours
Instructor Shane Steinert-Threlkeld GUG 415K and Zoom M 2:30-3:30PM Pacific
W 2:30-3:30PM Pacific
Teaching Assistant Saiya Karamali GUG 407 and Zoom T 2-4PM


The course textbook is Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, 2nd edition, by Daniel Jurafsky and James Martin.

A draft copy of the book is available here.

N.B.: The authors have a nearly-complete draft of the 3rd edition available online. Essentially every chapter that we use in this course has a corresponding version in that edition. The chapters referenced below are from the 2nd edition, but you can find the corresponding chapter in the 3rd edition either by using the website for the 3rd or by looking at the detailed table of contents on the Amazon page for the 2nd edition or here.


  • CSE 373 (Data Structures) or Equivalent
  • MATH/STAT 394 (Intro to Probability) or Equivalent
  • Formal grammars, languages, and automata
  • Programming in one or more of Java, Python, C/C++, or Perl
  • Linux/Unix Commands

Course Resources

N.B.: All homework grading will take place on the patas cluster using Condor, so your code must run there. I strongly encourage you to ensure you have an account set up by the time of the first course meeting.


Unless explicitly mentioned below, the shared policies of the LING 57x course series apply to this course. Please read those policies for more information.

We understand that you may face hard times as we navigate an ever-changing world due to the COVID-19 pandemic and many other world events. If you find yourself struggling with a difficult concept; stressed over politics or health; slowed by monopolistic internet providers; or annoyed at a classmate, please remember that they might feel similar. Maybe not in your very moment, but certainly recently or soon. Some of you may find the return to hybrid teaching conducive to your style of learning and personality. Others may find it stressful or difficult. These are all normal reactions. Please have compassion and empathy, and assume that everyone is doing their best.

If you find yourself having trouble learning in class, please do not hesitate to let me or Saiya Karamali know. Our goal is to make this class a bright spot in these unprecedented times, and to do whatever we can to promote a healthy learning environment for all.

A note on time zones

All deadlines and meeting times for this class are in "Pacific Time". Note that we will be moving the clocks back one hour on Sunday November 1. For the first part of this quarter, "Pacific Time" is UTC-7. After November 1, "Pacific Time" will be UTC-8. If you are in a part of the world that doesn't change the clocks twice a year or if your change is at a different time, please be aware that the time of day for classes & deadlines in your timezone will change on Nov 1.


  • 100%: Homework Assignments
  • Up to 2% adjustment for significant in-class or discussion participation
  • N.B.: Your lowest homework score will be dropped when calculating final grades.


As per the policy above, all communication outside of the classroom should take place on Canvas. You can expect responses from teaching staff within 24 hours, but only during normal business hours, and excluding weekends.

N.B.: while CLMS students have a private Slack channel, I strongly encourage questions concerning course content and assignments to be posted to the Canvas discussion board, for two reasons. (i) Teaching staff will not look at Slack, so misinformation can spread. (ii) Not every student in the course is in the CLMS program, but they deserve to be included in course discussions and likely have many of the same questions.

Religious Accommodation

Washington state law requires that UW develop a policy for accommodation of student absences or significant hardship due to reasons of faith or conscience, or for organized religious activities. The UW’s policy, including more information about how to request an accommodation, is available at Religious Accommodations Policy ( Accommodations must be requested within the first two weeks of this course using the Religious Accommodations Request form (

Access and Accommodations

Your experience in this class is important to me. If you have already established accommodations with Disability Resources for Students (DRS), please communicate your approved accommodations to me at your earliest convenience so we can discuss your needs in this course.

If you have not yet established services through DRS, but have a temporary health condition or permanent disability that requires accommodations (conditions include but not limited to; mental health, attention-related, learning, vision, hearing, physical or health impacts), you are welcome to contact DRS at 206-543-8924 or or DRS offers resources and coordinates reasonable accommodations for students with disabilities and/or temporary health conditions. Reasonable accommodations are established through an interactive process between you, your instructor(s) and DRS. It is the policy and practice of the University of Washington to create inclusive and accessible learning environments consistent with federal and state law.


Call SafeCampus at 206-685-7233 anytime – no matter where you work or study – to anonymously discuss safety and well-being concerns for yourself or others. SafeCampus’s team of caring professionals will provide individualized support, while discussing short- and long-term solutions and connecting you with additional resources when requested.


Date Topics + Slides Jurafsky & Martin Additional Readings Assignment out
Sept 27 Introduction; Syntax Chapter 1, 12 Patas and Condor HW1 [slides]
Due Oct 4
Oct 2 CFGs and Parsing Chapter 12, 13.1-13.3
SLP 3: Chapter 17, Appendix D
Oct 4 CKY; CNF Chapter 13.4.1
SLP 3: Chapter 17.6
  HW2 [slides]
Due Oct 11
Oct 9 Parsing: CKY Chapter 13.4.1; 14.1
SLP 3: Chapter 17.6
Oct 11 PCFGs: Algorithms and Evaluation
Earley parsing
Chapter 14.1-14.3; 14.7
Chapter 13.4.2
SLP 3: 17.8, Appendix C
  HW3 [slides]
Due Oct 18
Oct 16 PCFGs: issues and improvement Chapter 14.4 - 14.6
SLP 3: Appendix C
Oct 18 Dependency Parsing Chapter 12.7
SLP 3: Chapter 18
de Marneffe et al, 2006
McDonald et al, 2005
HW4 [slides]
Due Oct 25
Oct 23 Dependency Parsing (cont'd) + Features Chapter 15-15.4
SLP 3: Chapter 18
Oct 25 Semantics Intro Chapter 17
SLP 3: Chapter 19
  HW5 [slides]
Due Nov 1
Oct 30 Semantics (cont'd) Chapter 15.5-15.7; 17, 18    
Nov 1 More Lambda Calculus
Lexical Semantics
Chapter 18.2 Blackburn & Bos, 1999, 2.3–2.4 HW6 [slides]
Due Nov 8
Nov 6 Distributional semantics, I Chapter 19.1-19.3, 20.1-20.4, 20.7, 20.10
SLP 3: Chapter 23
Nov 8 Distributional semantics, II Chapter 20
SLP 3: Chapter 23
The Illustrated word2vec HW7 [slides]
Due Nov 15
Nov 13 Thesaurus similarity for WSD Chapter 19.4, 20.6, 20.9, 20.10
SLP 3: Chapter 23
Resnik WSD, esp. Sec 5.1
Nov 15 Semantic Role Labeling Chapter 19.4, 20.4; 21.0
SLP 3: Chapter 24
Jurafsky & Gildea, 2002, pp. 1-19. HW8 [slides]
Due Nov 22 29
Nov 20 Discourse: Reference Chapter 21.4-21.8
SLP 3: Chapter 26
Nov 22 No Class
Nov 27 Discourse: Structure Chapter 21.1-21.3
SLP 3: Chapter 27
Nov 29 Discourse: Reference Chapter 21
SLP 3: Chapters 26-27
HW9 [slides]
Due Dec 6
Dec 4 Overflow + case study    
Dec 6 Wrap-up: Unsupervised Learning, AMA