UPPSALA UNIVERSITET : Inst. f. lingvistik och filologi : STP
Uppsala universitet
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Schedule
Class Preparation
Examination
Assignments
Reading List
Course Evaluations


Natural Language Processing

Credits: 15 hp
Syllabus: 5LN710
Teachers: Joakim Nivre, Mats Dahllöf

News

Schedule

Date Time Room Content Reading
1
11/11
10-12
Chomsky
Introduction (slides)
J&M 1-2
2
12/11
15-17
Chomsky
Basic text processing (slides)
J&M 2-3
3
18/11
10-12
Chomsky
Probability and statistics (slides-1, slides-2, slides-3)
Schay
4
20/11
10-12
Chomsky
Language modeling (slides-1, slides-2, slides-3)
J&M 4
5
25/11
10-12
Chomsky
Part-of-speech tagging (slides)
J&M 5
6
27/11
10-12
Chomsky
Statistical models and algorithms (slides)
J&M 6
7
2/12
10-12
Chomsky
Syntax and statistical parsing (slides-1, slides-2, slides-3)
J&M 12-14
8
3/12
13-15
Turing
Dependency parsing (slides-1, slides-2)
KM&N
9
9/12
13-15
Turing
Lexical semantics (slides)
J&M 19-20
10
11/12
13-15
Turing
Computational semantics (slides)
J&M 17-18
11
16/12
10-12
9-2029
Applications: Presentations
J&M 22-25
12
18/12
10-12
9-2029
Applications: Presentations
J&M 22-25

Class Preparation

The course is based on active work in the classroom, which presupposes that students come prepared to each class, having read the relevant parts of the course literature in advance. During some weeks, there will also be video lectures to attend and quizzes to complete before the class. We use the Scalable Learning platform for this, so make sure to create a user account and sign up for the course using the enrollment key handed out by the teacher.

Examination

The course is examined by means of in-class exercises that are submitted as a single assignment once a week. In addition, students will survey an application area and present the result both orally and in writing.

In order to pass the course, the students must complete all assignments (including the oral and written presentation of the survey). In order to get pass with distinction (VG), at least half of the assignments have to meet the criteria for distinction.

NB: Participation in the in-class exercises is not mandatory but will greatly facilitate the completion of the assignments.

Assignments

  1. Basic text processing
  2. Probability and language modeling
  3. Statistical modeling and part-of-speech tagging
  4. Syntax and parsing
  5. Semantics and word sense disambiguation: Assignment
  6. Applications of NLP
    • Oral report: A 15-min introduction to an application area of NLP, based on at least two papers in addition to the textbook.
    • Written report: A 3-page introduction to an application area of NLP, based on the same material as the oral presentation.

NB: The deadline for handing in assignments is always the Monday of the following week.

Reading List

NB: Schay (2007) is my suggestion for those who do not already have a book on probability theory, but any introductory textbook on the topic will do fine.