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LING 388: Language and Computers. Sandiway Fong Lecture 1: 8/ 23. Administrivia. Where Social Sciences 224 When TR 3:30-4:45PM No Class Monday September 6 th (Labor Day) Office Hours catch me after class, or drop by my office (or make appt.) Location: Douglass 311. Administrivia.
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LING 388: Language and Computers Sandiway Fong Lecture 1: 8/23
Administrivia • Where • Social Sciences 224 • When • TR 3:30-4:45PM • No Class • Monday September 6th (Labor Day) • Office Hours • catch me after class, or • drop by my office (or make appt.) • Location: Douglass 311
Administrivia • Email • sandiway@email.arizona.edu • Class mailing list • ling388@listserv.arizona.edu • Homepage • http://dingo.sbs.arizona.edu/~sandiway • Lecture slides: • available on homepage after each class • in both PowerPoint (.pptx) and Adobe PDF formats • .pptxslides may contain animation • slides from Fall 2006 are available online • caution: there will be changes
Administrivia • Tips on how to take this class • No required textbook • Lecture slides contain everything you need to know in order to do the homeworks • To understand the slides, • you need to attend classes to “grok” the concepts • Unclear on something? • You are encouraged to ask questions in or after class • Ask while the question is still fresh in your mind • Practice • You can’t get good at computers just by reading a text • This is a hands-on class, try the exercises
Administrivia • Course Objectives • Theoretical • Introduction to natural language processing techniques • Practical • Be able to write a natural language grammar that runs on a computer • Get an idea of what’s hard and what’s easy to do on a computer Goal: by the end of the course, you will have built a small machine translation engine
Administrivia • Class demographics:
Administrivia • Laboratory Exercises • Some lectures will be laboratory sessions • We will do exercises on the computer in class • use your own laptop or workstation • Homework questions will be handed out in these sessions • Homework questions are designed to extend the exercises done in the lab • You may do the homework exercises on your own computer or at the computer laboratory
Grading 6~7 homeworks Mandatory and Extra Credit Questions: extra credit questions may be applied to the current homework they may also bump you up a grade if you are borderline at the end of the semester Homeworks are due 1 week after they are handed out Homeworks must be submitted by email to me (by midnight) Example: a homework given out on Wednesday will be due next Wednesday at midnight Ethics You may discuss the homeworks with your classmates However, you must do the work and write them up independently Sources must be acknowledged (students, webpage) Cheaters will be sanctioned Administrivia
Administrivia • Homework tips • Homeworks are based on lab exercises • make sure you show up for the lab lectures • Nightmare strategy: wait until the evening homework is due, scratch your head over the lecture notes, have tons of questions and start panicking • your computer crashes, the net goes down …
Administrivia • Late Policy • All homeworks are mandatory • deduction if handed in late • If you know you’re going to be late or have an upcoming emergency, let me know ahead of time
Administrivia • Homework Disaster Repair Policy • You “tank” on a homework • do badly or way worse than you expected • don’t panic • Strategies • always attempt any extra credit questions • get help and explanations from me • plus an extra question or two to demonstrate your understanding • Philosophy • You are not penalized for learning or making an unfortunate mistake
Natural Language Processing (NLP)Human Language Technology (HLT)Computational Linguistics • Research Question: • What methods can we use to process natural languages on a computer? • Intersects with: • Computer science (CS) • Mathematics/Statistics • Artificial intelligence (AI) • Linguistic Theory • Psychology: Psycholinguistics • e.g. the human sentence processor
Applications • Information retrieval • information is stored and accessed using language (keywords etc.) • document classification (email, news) • Machine translation • babelfish • http://babelfish.altavista.com/ • Google • Language Comprehension • document summarization • Speech • automated 800 toll-free directory (800 555 1212) • cellphones (handsfree dialing) • car navigation (voice-synthesized directions)
Applications • technology is still in development • computers can’t really understand language (yet) • seegooglewebpage translation or babelfish etc. • well, it’s free!
Applications • technology is still in development • even if we are willing to pay... • machine translation has been worked on since after World War II (1950s) • still not perfected today • why? • what are the properties of human languages that make it hard?
Natural Language Properties • Which ones are going to be difficult for computers to deal with? • Grammar (Rules for putting words together into sentences) • How many rules are there? • 100, 1000, 10000, more … • Portions learnt or innate • Do we have all the rules written down somewhere? • Lexicon (Dictionary) • How many words do we need to know? • 1000, 10000, 100000 …
Computers vs. Humans • Knowledge of language • Computers are way faster than humans • They kill us at arithmetic and chess • But human beings are so good at language, we often take our ability for granted • Processed without conscious thought • Do pretty complex things
Examples • Knowledge • Which report did you file without reading? • (Parasitic gap sentence) We take for granted this process of “fillingin” or recovering the missing information
Examples • Changes in interpretation • John is too stubborn to talk to • John is too stubborn to talk to Bill
Examples • Ambiguity • Where can I see the bus stop? • stop: verb or part of the noun-noun compound bus stop • Context (Discourse or situation)
Examples • Ungrammaticality • *Which book did you file the report without reading? • * = ungrammatical • relative • ungrammatical vs. incomprehensible
Example • The human parser has quirks • Ian told the man that he hired a story • Ian told the man that he hired a secretary • Garden-pathing • Temporary ambiguity • tell: someone something vs. …
Examples • More subtle differences • The reporter who the senator attacked admitted the error • The reporter who attacked the senator admitted the error • Processing time • Subject vs. object relative clauses • Q: Do we want to mimic the human parser completely?
Next time … • This Wednesday • We have our first lab class • Computers are based on logic and proceed via inference • Computer Language we’ll be using: • Name: PROLOG • Variant: SWI-PROLOG (free software) • Download: http://www.swi-prolog.org/ • Designed to express logic statements and phrase structure grammar rules
Your Homework for Today • Install SWI-Prolog on your PC • Read about Prolog online
Online Resources • Some background in logic or programming? • Useful Online Tutorials • An introduction to Prolog • (Michel Loiseleur & Nicolas Vigier) • http://boklm.eu/prolog/page_0.html • Learn Prolog Now! • (Patrick Blackburn, Johan Bos & Kristina Striegnitz) • http://cs.union.edu/~striegnk/learn-prolog-now/lpnpage.php?pageid=online