University of Toronto Computer Science 485
St. George Campus
Instructor : Lectures: Office: Tel: Office Hours: Email:
Summer 2020/First Session
CSC 485: Introduction to Computational Linguistics
Course Information
Gerald Penn
TR 1–3 Zoom
CSC485 Discord server
(416)978-7390
immediately following WF tutorials 2–3, or by appointment gpenn@teach.cs.utoronto.ca
Tutorials:
Teaching Assistants:
WF 1–2, Zoom
(Note: many tutorial days will be used for lectures) Name Assignment
Aditya Bhargava 1
Frank Niu 2
Textbooks : Required
Required
Recommended
Optional
Recommended
Jurafsky, Daniel, and Martin, James H. Speech and Language Processing, 2nd edition, Pearson Prentice-Hall, 2009. Available in paper and e-book rental versions (for the latter, go to CourseSmart.com and search for Jurafsky). We’ll also be referring to the draft 3rd edition: https://web.stanford.edu/∼jurafsky/slp3/. See also the errata list for the 2nd edition: www.cs.colorado.edu/∼martin/SLP/Errata/ SLP2-PH-Errata.html.
Bird, Steven; Klein, Ewan; and Loper, Edward. Natural Language Processing with Python, O’Reilly, 2009. Free (in HTML) with online extras at www.nltk.org/book.
Mertz, David. Text Processing in Python. Addison-Wesley, 2003. Free ASCII version at Gnosis.cx/TPiP.
Allen, James. Natural Language Understanding, 2nd edition. Benjamin/ Cummings, 1995.
Martelli, Ravenscroft and Holden. Python in a Nutshell, 3rd ed., O’Reilly, 2017.
Course Web Page: http://www.cs.toronto.edu/~gpenn/csc485/
Evaluation: There will be two homework assignments worth 45% of your course grade each,
and a final assessment essay worth 10%.
• No late homeworks will be accepted, except in case of documented medical or other emer- gencies.
Policy on collaboration: No collaboration on homeworks or essays is permitted. The work you submit must be your own. Failure to observe this policy is an academic offense, carrying a penalty ranging from a zero on the homework to suspension from the university.
Course Goals: This course is an introduction to a statistical and computational characteriza- tion of natural language. You will also have the chance to practice programming in Python.
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Prerequisites: STA247H1/ STA255H1/ STA257H1 and CSC209H1, but CSC324H1/ CSC330H1/ CSC384H1 is strongly recommended. Engineering students may substitute APS105H1/ APS106H1/ ESC180H1/ CSC180H1 for the CSC 209 requirement, although experience with the Unix operating system is strongly recommended, and/or ECE302H1/ STA286H1/ CHE223H1/ CME263H1/ MIE231H1/ MIE236H1/ MSE238H1/ ECE286H1 for the statistics requirement.
Note that the University’s automatic registration system does not check for prerequisites: even if you have registered for the course, you will not receive credit for it unless you had satisfied the prerequisite before you registered. For advice, contact the Undergraduate Office on the fourth floor of the Bahen Centre or the instructor.
Newsgroup: The course newsgroup is on the web at https://bb-2020-05.teach.cs.toronto.edu/c/csc485. Your teaching assistants will be monitoring it.
Tentative Syllabus:
Date
5–6 May 7 May 8–12 May
13–14 May
15–19 May
20–21 May 22 May 26–27 May 28–29 May 2 June
3–4 June 5–9 June 10–11 June 12 June
Topic
Intro to CL
Intro to NLTK and PyTorch Grammars and parsing
Chart parsing
Even More Parsing
Ambiguity resolution
Catch-up class if needed
Attachment models
Lexical semantics
Word sense disambiguation Statistical parsing Anaphora resolution Semantic representations Tutorial will meet as usual
Advance reading*
J&M: 1; BK&L: 1, 2.3, 4 as necessary BK&L: 1, 2.3, 4 as necessary
J&M: 5.0–1, 12.0–12.3.3, 12.3.7, 13.1–2; BK&L: 8.0–8.4
J&M: 13.3–4; A: 3.4, 3.6; BK&L: 8.4 and online extras section 8.2 on chart parsing J&M: 12.3.4–6, 15.0–3; A: 4.1–5;
BK&L: 9
J&M: 19.1–4, 20.8
J&M: 20.1–5
J&M: 5.2–5.5.2, 5.6, 12.4, 14.0–1, 14.3–7 21.0, 21.2–8
J&M: 17.0–17.4.1, 17.5; BK&L: 10.0–4
*J&M = Jurafsky and Martin; BK&L = Bird, Klein, and Loper; A = Allen; italics indicate optional additional reading.
Course Calendar:
Tue, 5 May Sun, 10 May Mon, 18 May Fri, 22 May Mon, 1 June Fri, 12 June Mon, 15 June Thu, 25 June
First lecture
Last day to add course Victoria Day
Assignment 1 due
Last day to drop course Last meeting
Assignment 2 due
Final assessment essay due
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