Course Information

  • Course: Working with Corpora, LIN392
  • Semester: Fall 2010
  • Course page: this page.
  • Course location: PAR 10.

Instructor Contact Information

  • office hours: Mon 1-3pm, Wed 3-4pm, or by appointment
  • office: Calhoun 512
  • phone: 471-9020
  • fax: 471-4340
  • email: katrin dot erk at mail dot utexas dot edu

Lab information

To get an account on the computational linguistics lab machines, please send me an email.

You can then log in remotely to iliad.ling.utexas.edu or odyssey.ling.utexas.edu.


Graduate standing.

Syllabus and Text

This page serves as the syllabus for this course.

There is no course textbook. Readings will be from the following resources available online:

Exams and Assignments

There will be four programming assignments and a project. For the project, there will be four separate parts that will be graded: a project proposal halfway through the semester, a progress report, an oral presentation on the project given during the final week of class, and a final report on the project. Evaluation will be based on the project and homeworks. There will be no exams.

Assignments will be updated on the assignments page. 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.

Philosophy and Goal

The goal of this course is to provide the student with the necessary tools and techniques for doing corpus-based studies and annotation projects. It will thus help prepare the student for doing original research using corpora.

Some specific goals of the course are to enable students to:

  • make an informed choice of data for a corpus study
  • specify an appropriate annotation format for an annotation project
  • understand and conduct evaluations of annotator performance
  • write programs for extracting and interpreting corpus data using the Python programming language
  • use the Natural Language Toolkit for automatic processing and analysis of corpus data
  • use search tools to extract occurrences of language phenomena from unannotated or annotated texts
  • perform a quantitative analysis of some corpus phenomenon
  • complete a non-trivial corpus-linguistic project and write a report

Content Overview

This course provides an in-depth introduction to the construction and use of corpora for linguistic analyses. It will adress the following points:

  • Making corpora:best practice for the collection of corpora
  • Annotating corpora: We will discuss annotation formats, annotation guidelines, and annotation evaluation, and we will look at concrete examples of corpus annotation projects.
  • Searching corpora: tools for extracting information from unannotated an annotated corpora
  • Quantitative analysis: a gentle introduction statistical analyses of corpus phenomena

The second topic of the course is an introduction to programming in Python. We will focus on using Python for corpus processing, including the use of the Natural Language Toolkit.

Course Requirements

  • Assignments (15% each): A series of 4 assignments will be given during the semester. Their purpose is to give you direct experience with the tools and techniques covered in class and the readings. Assignments will be done individually.
  • Project proposal draft (5%): Midway through the semester, you will propose a topic for your final project. There will be an opportunity to discuss your topic in advance during class. The proposal will be in written form and should be roughly 2-3 single-spaced pages.
  • Project progress report (5%): The progress report is mainly a revision of the proposal. It should take into account comments given on the proposal. Expect it to require significant rewriting, as opposed to just editing the proposal. In addition, it should include an update on progress to date.
  • Project final report (20%): The final report builds on the progress report and presents the project results and conclusions. It should be 4-8 pages in length.
  • Project presentation (10%): Each student will give a presentation on his or her project in the last week of class.

Extension Policy

If you turn in your assignment late, expect points to be deducted. Extensions will be considered on a case-by-case basis, but in most cases they will not be granted.

For other 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.

The greater the advance notice of a need for an extension, the greater the likelihood of leniency.

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. To determine if you qualify, please contact the Dean of Students at 471-6529; 471-4641 TTY. If they certify your needs, we will work with you to make appropriate arrangements.

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.