| Time: | T H 12:30-1:45 | Place | 426 Smith Hall |
| Professor: | Kathy McCoy | Office: | Room 201 77-79 E. Delaware Avenue |
| Office Hours: | T H 9:00-10:30, by appointment | ||
| Email: | mccoy@cis.udel.edu | Phone: | 302-831-1956 |
This course provides an introduction to the field of computational linguistics, also called natural language processing (NLP) - the creation of computer programs that can understand and generate natural languages (such as English). We will use natural language understanding as a vehicle to introduce the three major subfields of NLP: syntax (which concerns itself with determining the structure of an utterance), semantics (which concerns itself with determining the explicit truth-functional meaning of a single utterance), and pragmatics (which concerns itself with deriving the context-dependent meaning of an utterance when it is used in a specific discourse context). The course will introduce both knowledge-based and statistical approaches to NLP, illustrate the use of NLP techniques and tools in a variety of application areas, and provide insight into many open research problems.
Prerequisites: CISC681 - Introduction to Artificial Intelligence
Speech and Language Processing by Jurafsky and Martin. Please check the online errata for the text for each chapter as you read it. Please let me know if you find undocumented errors.
Grade Basis (approximate): homeworks (35%), project (25%), exams (35%), class participation (5%).
I will also keep a calendar that will be filled in as the semester goes on with the slides/materials for each specific lecture.
Please note that many of the materials/slides are borrowed from the NLP courses of Julia Hirschberg, Diane Litman, James Martin, and Johanna Moore. Also thanks also to Owen Rambow for the introduction to CFG's.
CALENDAR
| Date |
Topic | Reading | Assignments |
| 8/28 |
Course Overview, Introduction | Chapter 1 | |
| 8/30 |
Regular Expressions and Automata | Chapter 2, Perl
Introduction by Patrick Ryan |
Assignment 1
due 9/18 |
| 9/4 |
Regular Expressions and Automata (second part) | Chapter 2, Perl
Introduction by Patrick Ryan |
|
| 9/6 |
Finite Automata, Words, and the Lexicon | ||
| 9/11 |
Morphology and Finite State Transducers | Chapter 3 | |
| 9/13 |
N-Grams | Chapter 6 (through 6.4) | |
| 9/18 |
Continue with N-Grams |
Assignment 2
due 10/11
ASSIGNMENT 1 DUE |
|
| 9/20 |
More on N-Grams | ||
| 9/25 |
Word Classes and Part of
Speech Tagging
Print of Word Classes and Part of Speech Tagging |
Chapter 8 | |
| 9/27 |
More on Part of Speech Tagging | ||
| 10/2 |
Finish POS Tagging | Chapter 9 | |
| 10/4 |
NEEDED TO RESCHEDULE CLASS -- K. OUT!! | ||
| 10/8 |
Moved from 10/4 - Make-Up Class
Context-Free Grammars for English Print of Context-Free Grammars for English |
||
| 10/9 |
Finish Context Free Grammars |
Test Files for Assignment 2 Competition
ASSIGNMENT 2 TECHNICALLY DUE - Prepare spreadsheets for Thursday's class discussion |
|
| 10/11 |
Discussion of Assignment 2 -- Competition for NLP Belt |
Assignment 3
due 10/23
NEW: Test and Solution File for Assignment 3 Found Here |
|
| 10/16 |
NEED TO RESCHEDULE CLASS -- K. OUT OF TOWN!! | ||
| 10/18 |
Parsing with CFGs,
Print of Parsing with CFGs |
Chapter 10-10.3 | |
| 10/22 |
Make-up Class moved from 10/16
Finish Parsing with CFGs; Earley Algorithm Print of Earley Algorithm |
Chapter 10.4 | |
| 10/23 |
Features and Unification
Print of Features and Unification |
Chapter 11 |
Assignment 3 Due
Class Exam Due NEW DATE: 11/1 |
| 10/25 |
NO LONGER NEED TO RESCHEDULE CLASS -- K. NOT OUT OF TOWN!! | ||
| 10/25 |
Representing Meaning
Print of Representing Meaning |
Chapter 14 | |
| 10/30 |
Representing Meaning | Chapter 14 | |
| 11/1 |
Finish Representing Meaning;
Semantic Analysis
Print of Semantic Analysis |
Chapter 15 | NEW: Midterm Exam Due |
| 11/6 |
Finish Up sementic Analysis -- Intro to Compansion Project | ||
| 11/8 |
Discourse Processing: resolving anaphora, focusing, centering | ||
| 11/13 |
More Discourse: Centering, RAFT/RAPR, Pronoun Generation? | ||
| 11/15 |
CLASS PROJECT PRESENTATIONS | ||
| 11/20 |
CLASS PROJECT PRESENTATIONS | ||
| 11/22 |
HAPPY THANKSGIVING!! | ||
| 11/27 |
CLASS PROJECT PRESENTATIONS | ||
| 11/29 |
CLASS PROJECT PRESENTATIONS | ||
| 12/4 |
CLASS PROJECT PRESENTATIONS | ||
| ??? |
Final Class Project Due before 1:00pm | Final Reports Due | Project Reports |
| Topic | Reading | ||
| Course Overview, Introduction | Chapter 1 | ||
| Regular Expressions and Automata | Chapter 2, Perl
Introduction by Patrick Ryan |
||
| Words and the Lexicon | Chapter 2 | ||
| Morphology and Finite State Transducers | Chapter 3 | ||
| N-Grams | Chapter 6 (through 6.4) | ||
| Word Classes and Part of Speech Tagging | Chapter 8 (through 8.4) | ||
| Context-Free Grammars for English | Chapter 9 | ||
| Parsing with CFGs, | Chapter 10 | ||
| Earley Algorithm | Chapter 10 | ||
| Features and Unification | Chapter 11 | ||
| Representing Meaning | Chapter 14 | ||
| Semantic Analysis | Chapter 15 | ||
| Discourse | Chapter 18 | ||
| Natural Language Generation | Chapter 20 | ||
| Project Presentations | |||
| Probabilistic Models of Spelling | Chapter 5.1-5.6,
and pieces of the rest of chapter |
||
| More on Part of Speech Tagging | Chapter 8.5 - 8.7 | ||
| Lexicalized and Probabilistic Parsing | Chapter 12 | ||
| Lexical Semantics | Chapter 16 | ||
| Word Sense Disambiguation and Information Retrieval | Chapter 17 | ||
| Dialogue and Conversational Agents | Chapter 19 | ||
| Machine Translation | Chapter 21 |
Assignments must be your own individual work, unless explicitly stated otherwise. You must do the work without undue help from other people, and you must not present material from resources such as the Web, books, papers, code listings, and other people as your own. You may talk to each other about concepts and techniques, but you must not discuss specific solutions or approaches to solutions. Web resources will be very useful in this course and we will encourage class discussion of the use of such resources with their proper citations. Copying or paraphrasing someone's work, or permitting your own work to be copied or paraphrased, even in part, is not allowed and will result in an automatic grade of 0 for the assignment.
Classic NLP programs
Appelt and Israel's information extraction tutorial (IJCAI-99).
Allen's Dialogue Modeling for Spoken Language Systems tutorial (ACL Workshop 1997).