LIN350 Computational Semantics: Syllabus


Course Information

Instructor Contact Information

  • office hours: Mondays 1-3, Tuesdays 10-11
  • office: CLA 4.734
  • email: katrin dot erk at mail dot utexas dot edu

Teaching Assistant:

  • Manu Agarwal
  • office hours: Mondays 3:30-5:30
  • office: GDC 5.438F
  • email: manuag at cs dot utexas dot edu

Prerequisites

Upper-division standing. Introduction to Computational Linguistics OR Natural Language Processing OR consent of instructor.

Syllabus and Text

This page serves as the syllabus for this course.

Textbook: Patrick Blackburn and Johan Bos, "Representation and Inference for Natural Language. A First Course in Computational Semantics", CSLI Publications, ISBN 1575864967

Additional  readings will be made available for download from the course website.


Flags

This course carries the Quantitative Reasoning flag. Quantitative Reasoning courses are designed to equip you with skills that are necessary for understanding the types of quantitative arguments you will regularly encounter in your adult and professional life. You should therefore expect a substantial portion of your grade to come from your use of quantitative skills to analyze real-world problems.

This course also carries the Independent Inquiry flag. Independent Inquiry courses are designed to engage you in the process of inquiry over the course of a semester, providing you with the opportunity for independent investigation of a question, problem, or project related to your major. You should therefore expect a substantial portion of your grade to come from the independent investigation and presentation of your own work.

Exams and Assignments

Assignments will be updated on the assignments page. There will be 4 assignments.  A tentative schedule for the entire semester is posted on the schedule page. Readings and exercises may change up one week in advance of their due dates.

This is an Independent Inquiry course in which students do a course project that uses either a distributional model or logical form to address some language phenomenon. Requirements for the course project are: a short initial project description, an intermediate project report, a final project report, and a short in-class presentation. More details on the project requirements are listed on the assignments page.

This course does not have a midterm or final exam.

Attendance is not required. However, given that we will do a lot of hands-on exercises in class, and the homework assignments and the project address the material covered in class, good attendance is essential for doing well in this class.

Philosophy and Goals

Semantics is currently a very active area of computational linguistics -- but also a very diverse one. People work on word sense, semantic roles, selectional preferences, logic-based semantics and shallower approximations of it, as well as on many semantics-related tasks and task-specific semantic representations. But there are problems that come up again and again in different tasks, and representation ideas that come up again and again in different variants. In this course, we focus on two influential classes of representations: logic-based semantics and distributional semantics, and on central phenomena that they address.

Content Overview

This course focuses on two frameworks in semantics, distributional models and logic-based semantics. Topics include:

Distributional semantics:

  • Induction of distributional models from corpus data
  • Practical issues in computing distributional models
  • Variants: word embeddings and topic models
  • What does "similar" mean anyway?

Logic-based semantics:

  • Semantics construction
  • Typed lambda calculus
  • Inferences and theorem proving
  • Quantifiers and underspecification

We will also discuss possibilities for integrating the two approaches.

A detailed schedule for the course, with topics for each lecture, is available at the schedule page, which forms part of the syllabus.

Course Requirements and Grading Policy

  • Assignments: 60% (4 assigments, 15% each)
  • Course project:
    • Initial project description: 5%
    • Intermediate project report: 10%
    • In-class presentation: 5%
    • Final report: 20%

By default, course projects should be done by teams of 2 students; however, projects done by 1 or 3 students are possible with prior approval of the instructor.

Final grades will use plus/minus grades.

Extension Policy

If you turn in your assignment late, expect points to be deducted. Extensions will be considered on a case-by-case basis. In general, if you foresee problems with turning in an assignment on time, let the instructor know as soon as possible! The earlier we know, the better the chance that we can work out an extension without points deducted.

Also, if you are late with an assignment or with a document for the course project, and you are wondering whether you should still turn it in, the answer is yes. You will always get partial credit, plus you get to practice skills that are important for your success in the course.

If an extension has not been agreed on beforehand, then for assignments, by default, 5 points (out of 100) will be deducted for lateness, plus an additional 1 point for every 24-hour period beyond 2 that the assignment is late. For example, an assignment due at 2pm on Tuesday will have 5 points deducted if it is turned in late but before 2pm on Thursday. It will have 6 points deducted if it is turned in by 2pm Friday, etc.

Academic Dishonesty Policy

You are encouraged to discuss assignments with classmates. But all written work must be your own. Students caught cheating will automatically fail the course. If in doubt, ask the instructor.

Notice about students with disabilities

The University of Texas at Austin provides upon request appropriate academic accommodations for qualified students with disabilities. Please contact the Division of Diversity and Community Engagement, Services for Students with Disabilities, 471-6259.

Notice about missed work due to religious holy days

A student who misses an examination, work assignment, or other project due to the observance of a religious holy day will be given an opportunity to complete the work missed within a reasonable time after the absence, provided that he or she has properly notified the instructor. It is the policy of the University of Texas at Austin that the student must notify the instructor at least fourteen days prior to the classes scheduled on dates he or she will be absent to observe a religious holy day. For religious holy days that fall within the first two weeks of the semester, the notice should be given on the first day of the semester. The student will not be penalized for these excused absences, but the instructor may appropriately respond if the student fails to complete satisfactorily the missed assignment or examination within a reasonable time after the excused absence.

Emergency Evacuation Policy

Occupants of buildings on The University of Texas at Austin campus are required to evacuate buildings when a fire alarm is activated. Alarm activation or announcement requires exiting and assembling outside. Familiarize yourself with all exit doors of each classroom and building you may occupy. Remember that the nearest exit door may not be the one you used when entering the building. Students requiring assistance in evacuation shall inform their instructor in writing during the first week of class. In the event of an evacuation, follow the instruction of faculty or class instructors. Do not re-enter a building unless given instructions by the following: Austin Fire Department, The University of Texas at Austin Police Department, or Fire Prevention Services office. Information regarding emergency evacuation routes and emergency procedures can be found at http://www.utexas.edu/emergency.

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