CS 4705: Introduction to Natural Language Processing, Fall 2009



TTh: 2:40-3:55


 1024 Mudd


Kathy McKeown

Office Hours: 

Tu 4-5,We 4-5, 722 CEPSR





Teaching Assistant: 

Sara Rosenthal

Office Hours: 

M 5:30-6:30, 726 CEPSR

Th 1:30-2:30

Kaushal Lahankar

Th 4-5, TA Room, Mudd 122A

M 2-3





Announcements || Academic Integrity ||  Submission Directions || Description
Links to Resources || Requirements || Syllabus || Text


1.    Check Columbia Courseworks for announcements, your grades (only you will see them), and discussion. Professor McKeown and your TA will monitor the discussion lists to answer questions.

2.    If you are interested in doing NLP research projects for credit, please let Professor McKeown know. The NLP group often has research opportunities available. 




This course provides an introduction to the field of computational linguistics, aka natural language processing (NLP). We will learn how to create systems that can understand and produce language, for applications such as information extraction, machine translation, automatic summarization, question-answering, and interactive dialogue systems. The course will cover linguistic (knowledge-based) and statistical approaches to language processing in the three major subfields of NLP: syntax (language structures), semantics (language meaning), and pragmatics/discourse (the interpretation of language in context). Homework assignments will reflect research problems computational linguists currently work on, including analyzing and extracting information from large online corpora.



Speech and Language Processing, 2nd Editionby Jurafsky and Martin. It will be available from the University Bookstore, as well as from Amazon and other online providers. It should also be on reserve in the Engineering Library.



Four homework assignments, a midterm and a final exam. Each student in the course is allowed a total of 4 late days on homeworks with no questions asked; after that, 10% per late day will be deducted from the homework grade, unless you have a note from your doctor.  Do not use these up early!  Save them for real emergencies. 

All students are required to have a Computer Science Account for this class. To sign up for one, go to the CRF website and then click on "Apply for an Account".


Academic Integrity:

Copying or paraphrasing someone's work (code included), or permitting your own work to be copied or paraphrased, even if only in part, is not allowed, and will result in an automatic grade of 0 for the entire assignment or exam in which the copying or paraphrasing was done. Your grade should reflect your own work. If you believe you are going to have trouble completing an assignment, please talk to the instructor or TA in advance of the due date.










Sep 8

Introduction and Course Overview

 Ch 1



Sep 10

Natural Language and Formal Language: Regular Expressions and Finite State Automata

Ch 2, 3



Sep 15

N-grams and Language Models

Ch 4

 HW1 assigned

WSJ article


Sep 17

POS Tagging

Ch 5




Sep 22

HMMs and POS

Ch 6



Sep 24

Context-Free Grammars

Ch 12.1-12.14



Sep 29

Parsing with Context Free Grammars and Evaluation of POS taggers

Ch 13

HW 1 due


Oct 1

Probabilistic and Lexicalized Parsing

Presentation on using NLTK

Ch 14.1-14.7


 HW2 assigned

Where the Wild Things Are

NLTK Readme

POS guide

Text for the Stanford parser


Oct 6

Representing Meaning

Ch 17-17.2, 17.4



Oct 8

Semantic Analysis 

Ch  18.1-18.4



Oct 13

Semantic Analysis

Ch 19



Oct 15

Word Sense Disambiguation

Ch 20.1-20.5



Oct 20

Machine Learning Approaches to NLP and Introduction to Weka


 HW 2 due at midnight (err.. 11:59PM) on 10/21


Oct 22

Semantic Application and

Midterm Review



Oct 27

Midterm (midterm solutions)

Sample midterm



Oct 29

Words Eye




 Guest Speaker: Robert Coyne


Nov 3





Nov 5

Summarization, Weka slides

 Ch 23.3-23.7

 HW 3 assigned



Nov 10




Nov 12

Organizational Details

Information Extraction

Ch 22.1-22.4



Nov 17

Information Retrieval and Question Answering

 Ch 23.1-23.2



Nov 19

Pronouns and Algorithms for Reference Resolution

Ch 21.3-21.5

HW 3 due, 11:58PM, Sunday Nov. 22nd


EXTENSION: HW3 due 11:58 Nov. 25th


Nov 24

Text Coherence and Discourse Structure

Ch. 25

 HW 4



Dec 1





Dec 3

Machine Translation


Philipp Koehnís tutorial

Ch 21.1-21.2



Dec 8

Applications using discourse




Dec 10

The future and Final Review

A practice final exam


 HW 4 due, 11:58 pm, Dec. 13th









Dec. 15-16





Study Days


Dec. 17-23



Final Exams




Links to Resources (cf. also resources available from the text homepage):


1.    Karen Chung Language and Linguistics links

2.    CatSpeak

Places to look up definitions and descriptions of terminology:

1.    Oxford Dictionary of Linguistics

2.    Interesting Language Factoids and Non


Chapters 1 and 2:

Try out one of the many versions of Eliza on the web.


AT&T Labs - Research Finite State Machine Library

Later Chapters:

1.    Appelt and Israel's information extraction tutorial (IJCAI-99).

2.    Framenet.

Chapter 19:

1.    Ask Jeeves -- a search engine that answers questions in plain English.

2.    Answer Bus -- another Q/A system.

3.    Columbia's NewsBlaster summarizer

4.    IBM summarizer demo (canned)

5.    Systran machine translation (also in use at Babelfish)

6.    AT&T Labs - Research Finite State Machine Library

7.    Michael Collins' Parser

8.    On-line dictionaries in many languages.

9.    WordNet

10.                       Framenet

11.                       CoBuildDirect Corpus

12.                       AT&T's SCANMail voicemail browsing/search system

13.                       DiaLeague 2001 -- includes a link to an online dialogue system demo.

14.                       James Allen's Dialogue Modeling for Spoken Language Systems ACL 1997 Tutorial

15.                       Festival speech synthesizer demo and links to other TTS systems

16.                       Julia Hirschberg's Intonational Variation in Spoken Dialogue Systems tutorial

Announcements || Academic Integrity || Contributions || Description
 Links to Resources|| Requirements || Syllabus || Text