Deep Processing Techniques for NLP

N.B.: If you are a student, please refer to the course page on Canvas. This page is purely for public-facing informational purposes and is not guaranteed to be up-to-date.

Basic Info

Days Time Classroom
Mondays and Wednesdays 3:30—4:50PM DEN 212

 

Instructor Teaching Assistant
Name Ryan Georgi Ajda Gokcen
Office GUG 418-D GUG 416-A (Treehouse Lab)
Contact Use Canvas Inbox
Office Hours Wed 12:30-2:30 M/W 2:00–3:00 or by Appt.

Course Description

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

Textbook

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.

Prerequisites:

  • 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:

Grading:

  • 100%: Homework Assignments
  • Up to 2% Adjustment for significant in-class or discussion participation

Course Policies

Course Schedule

Date Topics Jurafsky & Martin Addt’l Reading Assignment Slides
Sep 26 Intro to Deep Processing for NLP; Syntax Chapter 1, 12 Patas and Condor HW #1 – 9/28 1 – Intro
Oct 1 CFGs and Parsing Chapter 12, 13.1—13.3 2 – Grammars
Oct 3 CKY; CNF Chapter 13.4.1 HW #2 – 10/5 3 – CKY
Oct 8 Parsing: CKY, Probablistic CKY Chapter 14–14.2 4 – PCKY & PCFG
Oct 10 PCFGs: Algorithms and Evaluation Chapter 14.2–14.6 HW #3 – 10/12 5 – PCKY & Eval
Oct 15 PCFGs: evaluation; improvement Chapter 14.7–14.11 6 – PCFG & Improvements
Oct 17 Dependency Parsing Chapter 12.7 De Marneffe et al, 2006
McDonald et al, 2005
HW #4 – 10/19 7 – Dependency Grammars
Oct 22 Dependency Parsing (cont’d) + Features Chapter 15–15.4 8 – OOV, Dep Parsing
Oct 24 Semantics Intro Chapter 17 HW #5 – 10/26 9 – Computational Semantics
Oct 29 Advanced Parsing Topics; Semantics (cont’d) Chapter 15.5–15.7; 17, 18 10 – More Computational Semantics
Oct 31 Lexical, Distributional Semantics Chapter 19.1–19.3, 20.1–20.4, 20.7, 20.10 HW #6 – 11/2
Nov 5 Distributional, Dictionary-based Models Chapter 20
Nov 7 Thesaurus similarity
Semantic roles & labeling
Chapter 19.4, 20.9 Resnik WSD, esp. Sec 5.1
Jurafsky&Gildea, 2002, p. 1-19.
HW #7 – 11/9
Nov 12 Veterans’ Day; No Class
Nov 14 SRL; Intro to Discourse Chapter 20, 21.0 HW #8 – 11/16
Nov 19 Computational Discourse Reference Chapter 21.4–21.8 Ragunathan et al, 2010
Nov 21 Computational Discourse Structure Ch. 21.1–21.3
Nov 26 TBD HW #9 – 11/30
Nov 28 TBD
Dec 3 TBD
Dec 5 Wrap-up