LING581: Advanced Computational Linguistics

Pre-requisities

This is the follow-on to the introductory course LING 538: Computational Linguistics.
(Note: 538 is Offered in Fall semesters only.)

Required

Both LING 538 and 581 are required for students enrolled in the HLT Master's Program.

Classroom: Place and Time

Spring semester 2019: Tuesdays and Thursdays 3:30-4:45pm. McClelland Park, Room 102.

Course Objectives and Description

This course continues LING/C SC/PSYC 538 Computational Linguistics and is a course designed also to give students more in-depth knowledge and hands-on experience with technique and software than is possible in 538.

Students will be expected to be able to gain enough familiarity to install, run and perform project work on these packages on their own machines.

Projects to be tackled in this course are themed around the topic of language understanding:

  1. Treebanks (phrase-structure/dependency-based): e.g. Penn Treebank, lookup software.
  2. Part-of-speech taggers.
  3. The use and modification of statistical parsers trained on Treebanks
  4. Advanced linguistic theories
  5. Ontologies and Semantic Networks: WordNet etc.
  6. Question-Answering (QA)
  7. more...

Grading

Students will be given a series of tasks to accomplish. Completion of all tasks will result in a satisfactory grade.

Reading and Computational Resources

Required reading will be from the 538 course textbook Speech and Language Processing (Jurafsky & Martin), and in the form of project documentation (manuals) and papers and/or dissertations to be made available on-line.

Students are expected to install required software (all available freely) on their own machines.


Lecture Schedule

January

Date Lecture Notes Number
of Slides
Panopto Topic
PDF Powerpoint
1/10 lecture1.pdf lecture1.pptx 26 link Syllabus, Homework 1: install Python 3 and nltk (if not already present).
1/15 lecture2.pdf lecture2.pptx 22 link Homework 2 on nltk. Loading your own corpus. Example: Mrs. Dalloway by Virigina Woolf.
1/17 lecture3.pdf lecture3.pptx 13 link Named Entity Recognition and Google Cloud Natural Language. Sentiment/magnitude scores. Dependency parses. Quick Homework 3.
1/22 lecture4.pdf lecture4.pptx
1/24 lecture5.pdf lecture5.pptx link
1/29 lecture6.pdf lecture6.pptx link
1/31 lecture7.pdf lecture7.pptx link

February

Date Lecture Notes Number
of Slides
Panopto Topic
PDF Powerpoint
2/5 lecture8.pdf lecture8.pptx link
2/7 lecture9.pdf lecture9.pptx link
2/12 lecture10.pdf lecture10.pptx link
2/14 lecture11.pdf lecture11.pptx link Guest lecture: Tatjana Scheffler.
2/19 lecture12.pdf lecture12.pptx link
2/21 lecture13.pdf lecture13.pptx link
2/26 lecture14.pdf lecture14.pptx link
2/28 lecture15.pdf lecture15.pptx link

March

Date Lecture Notes Number
of Slides
Panopto Topic
PDF Powerpoint
3/5 Spring recess: no class.
3/7 Spring recess: no class.
3/12 lecture16.pdf lecture16.pptx link
3/14 lecture17.pdf lecture17.pptx link
3/19 lecture18.pdf lecture18.pptx link
3/21 lecture19.pdf lecture19.pptx link
3/26 lecture20.pdf lecture20.pptx link
3/28 lecture21.pdf lecture21.pptx link

April

Date Lecture Notes Number
of Slides
Panopto Topic
PDF Powerpoint
4/2 lecture22.pdf lecture22.pptx link
4/4 lecture23.pdf lecture23.pptx link
4/9 lecture24.pdf lecture24.pptx link
4/11 lecture25.pdf lecture25.pptx link
4/16 lecture26.pdf lecture26.pptx link
4/18 lecture27.pdf lecture27.pptx link
4/23 lecture28.pdf lecture28.pptx link
4/25 lecture29.pdf lecture29.pptx link
4/30 lecture30.pdf lecture30.pptx link


To my linguistics homepage