Natural Language Processing (202-2-5211)

News:

1. March 22nd: Assignment 1 is available
2. May 31st: Assignment 2 is available

1. General Intro to NLP - Linguistic Concepts
2. Parts of speech Tagging
3. Context Free Grammars Parsing
4. Automatic Text Summarization

1. Language Models and n-grams -- Statistical Models of Unseen Data (Smoothing)
2. Information Extraction / Named Entity Recognition
3. Using Machine Learning Tools: Classification, Sequence Labeling / Supervised Methods / SVM
4. Compositional Semantic from CFG Parsing
5. Sentence Simplification

• Assignment 1: Tagging
• Assignment 2: Chunking, Named Entity Extraction and Classification

• NLTK Installation: Nltk is a Python based toolkit with wide coverage of NLP techniques - both statistical and knowledge-based.
• SISC Scheme Interpreter: we use Scheme examples to demonstrate algorithms in parsing, generation and some semantic analysis. This interpreter is very small and convenient to use on any platform supporting Java (full version is 2.4MB with full doc - jar is 300KB).

• Bob Carpenter's Computational Linguistics Syllabus - Excellent collection of references in the field.
• The LingPipe Java library suite - by Bob Carpenter. Information extraction and data mining tools.
• The NLTK Toolkit - Python toolkit with thorough tutorial on all Natural Language topics.
• Introduction to Natural Language Processing, bySteven Bird, Ewan Klein and Edward Loper, 2009, distributed on the NLTK site.