CSEP 517 - Natural Language Processing

University of Washington Department of Computer Science & Engineering

CSEP 517 - Natural Language Processing - Autumn 2013
Wed 6:30-9:20pm in MGH 231

CSE Home

About Us

Contact Info

Instructor: Luke Zettlemoyer (lsz at cs dot washington dot edu)
Office hours: After class, until everyone leaves TAs:
Yoav Artzi (yoav at cs dot washington dot edu)
Janara Christensen (janara at cs dot washington dot edu)
Anthony Fader (afader at cs dot washington dot edu)
Mark Yatskar (my89 at cs dot washington dot edu)
Office hours: Wed 5:30-6:30, CSE Third Floor Breakout (Open area by elevators)

Schedule [WARNING: topics subject to change!]

Week	Dates	Topics & Lecture Slides	Notes (required reading)	Textbook (recommended reading)	Academic Papers (optional reading)
1	Sep 25	Introduction; Language Models (LMs)	LM Notes	J&M 4; M&S 6	[Smoothing] [Pitman-Yor] [Large LMs]
2	Oct 2	LM (cont.); Text Classification: Naive Bayes and Linear Models	Naive Bayes (Sec. 1-4), Log-linear models (Sec 2)	J&M 20-20.4; M&S 16.2-16.3	[Semi-supervised Naive Bayes] [MaxExt]
3	Oct 9	Hidden Markov Models (HMMs)	HMM Notes	J&M 5.1-5.3, 6.1-6.4; M&S 9, 10.1-10.3
4	Oct 16	POS and Feature Rich Tagging	CRF Notes		[TnT Tagger] [Stanford Tagger] [SOTA POS]
5	Oct 23	POS (cont.); EM and Semi-supervised learning	Naive Bayes (Sec. 4-6)
6	Oct 30	PCFGs and Parsing	PCFG Notes Lexicalized PCFGs	J&M 14; M&S 11-12	[Lexicalized] [Unlexicalized] [Split Merge]
7	Nov 6	Parsing(cont.); Word Alignment; Phrase-based MT	IBM Models 1 and 2 Phrase-based Notes	M&S 13; J&M 25.1-6;J&M 25.7-9	[IBM Models] [HMM Model] [Phrase-based Model] [Decoding] [Tuning]
8	Nov 13	Compositional Semantics		J&M 17.1-4
9	Nov 20	Phrase-based MT (cont.); Syntax-based MT		J&M 22.1-2	[Tree-to-String] [Hiero] [Tree-to-Tree] [Reordering]
10	Nov 27	No class. Happy Thanksgiving!
11	Dec 4	Discourse and Co-reference; TA Research Talks		J&M 21.2-8

Textbooks

Recommended: D. Jurafsky & James H. Martin, Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition, Prentice Hall, Second Edition, 2009. (J&M)
Optional: C.D. Manning & H. Schuetze, Foundations of Statistical Natural Language Processing, Cambridge: MIT Press, 1999 (available online, free if accessed from UW computers) (M&S)

Contact

Please feel free to email the course staff, addresses above, and come to office hours. Let us know if you need to meet outside of the scheduled hours, we will do our best to accomodate.
We also have a GoPost discussion board. Please consider posting your questions there; everyone will benefit. We also encourage you to try to answer questions, which will count as class participation. We will monitor daily and contribute as long as the boards are being used.
Grades: Assignment grades are posted in the online CSEP 517 Gradebook. Please let us know if you see any errors.

Homeworks

We will have 4 programming assignments, which will be listed below as they are assigned. All code and data for these assignments are available in the course ShareSpace. Look here for some hints and guidelines about how to do a good writeup.

Assignment 1: Language Models [pdf] (Due Tue Oct 15, 11:45pm)
Assignment 2: POS Tagging [pdf] (Due Tue Oct 29, 11:45pm)
Assignment 3: Parsing [pdf] (Due Fri Nov 22, 5pm)
Assignment 4: MT [pdf] (Due Fri Dec 13, 5pm)

Please submit your assignments to the online DropBox.

Grading

The final grade will be based on the four homeworks (25% each). There will be no exams.

Course Administration and Policies

Assignments must be done individually unless otherwise specified. You may discuss the subject matter with other students in the class, but all final answers must be your own work. You are expected to maintain the utmost level of academic integrity in the course.
Assignments may be handed in up to one week late. You have 8 free late days that can be used across the assignments in any combinartion without penalty. After you have used the free days, we will subtract 10% of the maximum grade per day.
Comments can be sent to the instructor and/or TAs using this anonymous feedback form. We value your feedback!

Department of Computer Science & Engineering
University of Washington
Box 352350
Seattle, WA 98195-2350
(206) 543-1695 voice, (206) 543-2969 FAX