Using Corpora

A short course to be held as part of the Masters Course
 Lingüística Inglesa: Nuevas Aplicaciones y Comunicación Internacional
Universidad Complutense de Madrid
7-9 April 2010

Tutor: Dr. Adam Kilgarriff
Lexical Computing Ltd.
Brighton, UK

PROGRAMME

Weds 7th, 1500-16.45
Why we need corpora and how to build them

Over the last twenty years, we have seen a completely new way of studying language: by looking at corpora.  We can ask and answer questions that seemed impossible before.  The new possibilities arise because of computers: computers to process texts with, and computers that people write and publish texts on so there are large quantities of electronic text available.  We need tools to work with corpora and in this lecture I will introduce the Sketch Engine, a leading tool, and show what is possible, including giving a practical session.

Reading: 
  John Sinclair
    Reading Concordances. Longman 2003
    Corpus, Concordance, Collocation. Oxford University Press 1991
  McEnery and Wilson
    Corpus Linguistics, Second Edition, 2001: Chapters 1, 3.1-3.3, 4.3.
  Wikipedia (try also Spanish versions)
    Corpus Linguistics http://en.wikipedia.org/wiki/Corpus_linguistics
    Collocation http://en.wikipedia.org/wiki/Collocation

Weds 7th, 17.15-19.00
Web corpora

The web is, amongst many other things, a vast supply of electronic text of all varieties and languages. I will explore the potential and hazards of using the web as a source of language data for the linguist and will show a range of ways in which the web can be used including a demo, and then a hands-on session, showing how we can build a small specialist corpus of a text type we are studying, using the WebBootCaT tool, in a few minutes.

Reading:
Adam Kilgarriff and Greg Grefenstette
  Introduction to the Special Issue on Web as Corpus.  Computational Linguistics 29 (3)  2003: online at  http://kilgarriff.co.uk/publications.htm

Thurs 8th, 15.00-18.00

Corpus Processing and NLP

If we want to use corpora to study syntax and the lexicon, it is very helpful to know which words are nouns, which verbs, etc, and also to study lemmas (dictionary headwords, invade) rather than word forms (invade invading invades invaded) and to identify grammatical relations, for example the head noun that is the object of a verb.  This is all possible using methods and programs from NLP (Natural Language Processing, also known as Computational Linguistics, Language Technology). I will introduce the critical methods from NLP and show how they are applied to add value to English and Spanish corpora in the Sketch Engine.  
 
I will also present the research programme of ‘corpus driven computational linguistics’, in which we use data-driven methods to apply richer and richer analyses of texts, with the eventual (but far-off) goal of being able to make inferences directly from the texts that we analyse.

There will be a practical exercise on part-of-speech tagging.

Reading:
   Jurafsky and Martin
     Speech and Language Processing. Prentice Hall. Chapters 1.1-1.5, 2.1, 3.1, 8.1-8.4.
  McEnery and Wilson
     Corpus Linguistics, Second Edition, 2001: Chapters 2, 5.1-5.5
   Wikipedia (very short intros)
      Computational Linguistics http://en.wikipedia.org/wiki/Computational_linguistics
      Lemmatizer http://en.wikipedia.org/wiki/Lemmatizer 
      POS-tagging  http://en.wikipedia.org/wiki/Part-of-speech_tagging

Fri 9th, 15.00-1800
Word Senses

Many words have more than one meaning.  But, for any particular word, how many meanings does it have? Do dictionaries agree on the answer? If not, why not?  What are word meanings?  What role do they have in linguistics and in language technology?

I shall discuss the relation between dictionaries and lexicon, and present software for semi-automatic lexicography where we give maximum computational support to the process of identifying and disambiguating word meanings in text.

There will be a practical exercise on word sense tagging.

Reading:   Kilgarriff
•	"I don't believe in word senses" Computers and the Humanities 31: 91-113.
•	Word Senses. In Word Sense Disambiguation: Algorithms and Application, ed. Agirre and Edmonds. Chapter 2, pp 29-46. Springer.
Both online at http://kilgarriff.co.uk/publications.htm