Language Technologies Institute
11-712: Self-Paced Laboratory

Algorithms for NLP:
Introduction

To receive credit for this course, you must complete three self-paced lab modules, which are related to the material presented in 11-711, Algorithms for NLP. Self-contained instructions are included with each module. You can work on the modules in any order you choose. However, please note that the lab modules tend to parallel the lecture material, so it might be better to do them in order if you are new to the material and taking the course at the same time.

You are encouraged to complete the modules as early as possible and have them evaluated; since you have until the end of the semester to hand in final versions, you will have the opportunity to correct mistakes if you hand in early.

Typically, you are provided with a description of a language processing technique, and some existing code, knowledge, and test data; your work is to code up additional programs and/or knowledge to solve a particular problem.

The programming language for the course is Common Lisp. GNU Common Lisp is available on LTI lab machines (/usr/local/bin/gcl); a variety of Common Lisps are available on other SCS platforms. Students who have ready access to non-lab machines which run Common Lisp are encouraged to use them when working on their modules; all the given code and knowledge will be available in AFS. If you're not sure whether your machine supports Common Lisp, please contact the instructor for advice.

This course assumes working knowledge of Common Lisp. Students with no prior experience in Common Lisp will have difficulty completing the course, especially the first module; please contact the instructor.

If your Lisp skills are rusty and you would appreciate a review, please contact the instructor; if enough students show interest, we may hold an informal review session.

You should follow these steps in completing each module:

  1. Read all of the instructions and background material provided for the module, both the web pages and any handouts provided separately.

  2. If any parts of the instructions are unclear, contact the instructor for clarification before you begin coding.

  3. Code up your solution(s), using the provided test code and examples to verify the correctness of each solution.

  4. Hand in your code and test results by copying your file(s), which honor the designated file naming convention(s), into the subdirectory which corresponds to your userid under:

    /afs/cs/project/cmt-55/lti/Lab/Modules/NLP-712/handin/

  5. Send EMail to the instructor when your work is complete and you are ready to have it evaluated.

NOTE: For Spring Semester 2002, the last day to complete your work, hand it in, and notify the instructor is Friday, May 02, 2003.

09-Sep-98 by ehn@cs.cmu.edu ~~~~ 14-Jan-03 update by alavie@cs.cmu.edu