Disclaimer: This class is undergoing redevelopment, and the syllabus may change as the semester progresses.

Required readings are mostly drawn from the 3rd (forthcoming) edition the 2nd (2008) edition of Jurafsky and Martin's Speech and Language Processing textbook. Note that the numbering of the chapters has changed between those editions.

Optional readings are often more advanced. "MS" refers to chapters in Manning and Schütze (1999), Foundations of Statistical Natural Language Processing (you may need to use a campus machine to access the links to the chapters below) or to original research papers (you can find many more on the ACL anthology). I also recommend the Handbook of Computational Linguistics and Natural Language Processing (you also need to be on the campus network to access this site).

Lecture slides and Assignments are also linked to on this page. We typically release assignments in the evening of the day they come out. Assignments assume familiarity with Python 3.

Schedule

(MP1 due 09/30)
Wed, 08/28 01 Introduction pdf
   What is NLP? What will you learn in this class? How will we teach this class?
   Required reading: Ch.1 (2nd Ed).
   Optional reading: Python tutorial (sec. 1-5), Jelinek (2009), Ferrucci et al. (2010)
 
Fri, 08/30 02 Regular Expression and Tokenization pdf
   Review of finite-state automata, Finite-state transducers, tokenization
   Required reading: Ch. 2
 
(Video) 03 Language Models; Intro to Probability Models for NLP (video) pdf
  Review of basic probability. How do we apply these ideas to NLP?
   N-gram language models. Evaluation: Perplexity and Word Error Rate.
   Required reading: Ch. 3
   Optional reading: MS, Ch. 2
 
Wed, 09/11 04 Introduction to Classification for NLP pdf
  Binary and Multiclass classification for NLP. Naive Bayes
   Required reading: Ch. 4
 
Fri, 09/13 05 Logistic Regression for NLP pdf MP1 out
   Another way to do classification in NLP.
   Required reading: Ch. 5
 
Wed, 09/18 06 From Logistic Regression to Neural Nets pdf
  Feedforward networks, neural language models
  Required reading: Ch. 7
 
Fri, 09/20 07 More basic neural nets for NLP pdf
   More on neural models for NLP
   Required reading: Ch. 7
 
Wed, 09/25 08 Distributional similarities and Vector Semantics pdf
   Representing words as vectors
   Required reading: Ch. 6
 
Fri, 09/27 09 Word Embeddings and basic intro to RNNs pdf MP2 out
   Introduction to POS tagging
   Required reading: Ch. 8
 
Wed, 10/02 10 Part of Speech Tagging I pdf
   POS tagging
   Required reading: Ch. 8
 
Fri, 10/04 11 More on POS tagging and Sequence Labeling pdf [4Cr] Proposal due
   Required reading: Ch. 8
  
 
Wed, 10/09 12 Review for midterm pdf
   NB: Please go over the material before class by yourself
 
Fri, 10/11 13 Midterm Exam
   In-class midterm
 
Wed, 10/16 15 Machine Translation I pdf
   Introduction to Machine Translation
 
Fri, 10/18 16 Machine Translation II pdf MP2 due. MP3 out
   More on Machine Translation
   Optional reading: Brown et al. (1990), Lopez (2008), Koehn et al.,
   Och& Ney (2004), Wu (1997), Chiang (2007) www.statmt.org
 
Wed, 10/23 17 Syntax and Parsing I: Constituencies and Dependencies pdf
   Formal Grammars for English
   Required reading: Ch 12
   Optional reading: MS, Ch. 3, Woods (2010)
 
 
Fri, 10/25 18 Syntax and Parsing II: Constituency Parsing pdf
   PCFGs and CKY Parsing
   Required reading: Ch 13
   Optional reading: Collins' notes, Chi & Geman (1998), Schabes et al. (1993),
   Schabes & Pereira (1992), Stolcke (1995), Marcus et al. (1993), Collins (1997),
   Johnson (1998), Klein & Manning (2003), Petrov & Klein (2007), Hindle & Rooth
 
Fri, 11/01 19 Syntax and Parsing III: Dependency Parsing pdf
   Dependency Grammar and Shift-Reduce Dependency Parsing
   Required reading: Ch. 13 (3rd ed), McDonald & Nivre (2007)
   Optional reading: Nivre & Scholz (2004), Kubler et al. (2009), Nivre (2010), McDonald & Nivre (2011)
 
Wed, 11/06 20 Interlude: More on RNNs pdf
   More on RNNs: seq2seq models
   Required reading: Ch 10
 
Fri, 11/08 21 Syntax and Parsing IV: Expressive Grammars pdf [4Cr] Progress Report due
   Going beyond CFGs (with a focus on categorial grammars)
   Optional reading: Abney (1997), Miyao & Tsujii (2008), Joshi and Schabes (1997),
   Steedman & Baldridge (2011), Schabes & Shieber, Schabes & Waters (1995),
   Bangalore & Joshi (1999), Hockenmaier & Steedman (2007), Clark & Curran (2007)
 
Wed, 11/13 22 Sentence Semantics I: Compositional Semantics pdf
   What is the meaning of a sentence, and how can we represent it? Basic predicate logic and lambda calculus
   Required reading: Ch. 14
   Optional reading: Blackburn & Bos (2003), The Lambda Calculator
 
Fri, 11/15 23 Thesaurus-based Lexical Semantics pdf
   Lexicographic approaches to Lexical Semantics (WordNet etc.)
   Required reading: Ch. 19
  
 
Wed, 11/20 24 Verb Semantics and Semantic Role Labeling pdf
 
   Basic intro to verb semantics: events, thematic roles, SRL 
   Required reading: Ch. 20
 
 
Fri, 11/22 25 Discourse pdf
   Referring expressions/coreference, rhetorical/discourse relations 
   Required reading: Ch. 22 and Ch. 23
 
Wed, 12/04 27 Dialogue pdf
 
Fri, 12/06 28 Review for final exam pdf MP4 due.
  We'll go over the material after the midterm
 
Wed, 12/11 29 Final exam (in-class)
 
Fri, 11/08 22 Sentence Semantics II: Semantic Role Labeling pdf MP3 due. MP4 out   How do we represent and capture who does what to whom?   Required reading: Ch. 18   Optional reading: Palmer et al. (2005), Gildea & Jurafsky (2002), Punyakanok et al. (2008)   Wed, 11/13 23 Discourse I pdf   Entities and Coreference   Optional Reading: Grosz et al. (1995), Poesio et al. (2004), Barzilay and Lapata (2008)   Fri, 11/15 24 Discourse II pdf   What does it take for a text to make sense?   Wed, 11/20 25 Dialogue I pdf   Fri, 11/22 26 Dialogue II pdf   Wed, 12/04 27 TBD pdf