Download - Corpus annotation and retrieval: an introduction Paul Rayson Computing Department, Lancaster University Dawn Archer School of Humanities, University of

Corpus annotation and retrieval: an introduction

Paul RaysonComputing Department, Lancaster University

Dawn ArcherSchool of Humanities, University of Central Lancashire

Text Mining for HistoriansJuly 17-18 2007 Glasgow University

Session outline

What is a corpus?

What is corpus linguistics?

Applying these techniques to historical data

What research questions can we answer with CL techniques

… in linguistics …?… in computing …?… in history …?

1. Background

Corpora, corpus linguistics, annotation, retrieval methods


Underlying assumption

Intuition is not enough to study language …

Reaction to Noam Chomsky’s focus on introspection in 1950s/60s

Empirical observation of naturally occurring data versus theory of how

human language processing is actually undertaken


What is a corpus?

Old meaning = “body of text” (Latin)

Now = (any) “collection of texts or language examples” – usually in an electronic format

Demonstrates extent to which CL-revival led by advances in computing technology


A corpus tends to be “representative”

i.e. a balanced sample of a language or a particular variety of language --- c.f. national corpora (British, American, Czech, Polish …)

Reasoning? Helps to remove intuitive bias Helps us to find common/ rare phenomena

Exceptions …?


And large …

… because size helps us to:

Establish norms about the variety being studied

Reveal lots of cases of rare features of language

Zipf’s law


Size matters!

Brown/LOB1960s1 million

BNC1990s100 million

WebPresent day? billion


Birmingham corpus198010 million

Collins Bank of EnglishCambridge International CorpusOxford English Corpus2006600 million – 1 billion

WebFuture? billions


So what is corpus linguistics?

= the “study of language using corpora”

= empirical methodology

= a useful means of exploring: Synchronic and diachronic variation Syntax, semantics, pragmatics Lexicography Dialects, minority languages Not just English


Corpus techniques we utilise

Retrieval

Frequency profiling Concordancing Collocations Key words Key domains

Annotation

POS tagging Semantic tagging


Annotation Part of speech

tagging Semantic field

tagging

Retrieval Frequency

lists Concordances


Key words

Text

Keywords

Text or reference corpus

What are “key words”?And why are they so useful?


Key words

Word Clouds

If we compare text A

… with text B … we can discover the most significant items within text A

… and not only the frequent items


Collocations

Collocation = a relationship between words that tend to occur together in texts

Words that tend to occur near word X are the collocates of word X (consider “fish and XXXXX”)

Based on frequency (how frequent separate vs. how frequent together)

The company a word keeps: implicit associations or assumptions

Bachelor: eligible, flat, life, days Spinster: elderly, widows, sisters, parish


Corpus software


Modern methods in an historical setting (focussing on EmodE period)

Tools/methods don’t take account of spelling variation Variant spelling detector (VARD)

The need to use historically valid taxonomies or thesauri, or revise our existing modern tagsets Historical Thesaurus of English Spevack (1993)


Using automated systems of annotation on historical texts is problematic …

EModE texts pose the following “problems”: Archaic –eth and –(e)st verb suffixes, e.g. doth, hath,

hast, sayeth, etc., which persist in specialised contexts: religious and poetic usage

Fused forms, e.g. ’Tis (It is) Spellings that are variable even in modern-day usage,

e.g. center/centre, skilful/skillful/skilfull, the suffixes -or/-our, -ise/-ize

Archaic forms like howbeit, betwixt, for which no obvious modern equivalent exists

Compound words, e.g. it self, now adays, in stead Proper names of Latin origin that are sometimes

modernised, e.g. Galilaeo (Galileo) Due to different conventions and compositing practices


Previous work in …

Fuzzy search engine Aimed at successful

retrieval for novice users without expertise in the text

Expand the search term using known letter replacements

Changing dictionary built in to corpus annotation software

Back-dating inbuilt dictionaries by adding historical variants

Information Retrieval

Corpus linguistics

Natural language processing


Our scenario

SEM TAGGER

POS TAGGER

VARD: Detect variant spellings

and insert modern equivalents


An important point about the VARD

Although the VARD allows for the detection and “normalisation” of variants to their modern equivalents, it should be noted that ...

The original variants are retained in the text We’re not carrying out spell checking per se (no

“correct” spelling in EmodE period) ...

Our ultimate aim is to develop a system that automatically regularises variants within a text to their modernised forms so that historical corpora become more amenable to further annotation and analysis.

2. Historical data


Existing corpora

What is already available: LOB-family, Brown family (20th Century)

15 genres: press, religion, skills & hobbies, biography, learned, fiction (detective, science, adventure), romance, humour

Lampeter (1640-1740) Religion, Politics, Economy, Science, Law and Misc.

Corpus of English Dialogues (1560-1760) Trial proceedings, depositions, drama, prose fiction

Helsinki (Old, Middle and Early Modern English) Archer (1650-1990, sampled at 50 year periods)

Journals, letters, fiction, news, medicine, science


Book Search

Other historical texts – not complied for corpus linguistics


Changing English Across the 20th Century: a corpus-based study ucrel.lancs.ac.uk/20thCenturyEnglish/ Leverhulme Trust (2005-7)

1901 1931 1961 1991/2

BrE Lanc-1901 B-LOB

(Lanc-1931)

LOB F-LOB

AmE ? Pre-Brown31

Brown Frown

Background:

Recent observations of significant shifts having occurred among expressions of obligation/necessity in the period 1961-1991 e.g.

• a decline of the central modals MUST and NEED • a spread of the semi-modals HAVE TO, NEED TO

Research questions

? Are these changes recent? How do these changes

compare to the development of the semantic field of OBLIGATION/ NECESSITY as a whole?

Project outputs

• Compile a new corpus of British English called Lancaster1901• Enhance the encoding and annotation of Lancaster1901 and the three existing corpora (Lancaster1931, LOB and FLOB)• 10 conference presentations• 1 book chapter• 1 book• 2 journal articles

Application 2: Historical CL

In particular, courtroom research (1640+), from a linguistic perspective

Utilise a specially designed corpus – Sociopragmatic Corpus – which has been annotated for: age, gender, status and

role. speech acts such as

questions, requests and commands

 [$ (^Record.^) $] <u stfunc="fol-ini" force="q" q="qy" qtype="d" qform="dec" speaker="s" spid="s4tgiles001" spsex="m" sprole1="re" spstatus="1" spage="8" addressee="s" adid="s4tgiles027" adsex="f" adrole1="w" adstatus="5" adage="x">He did not go out of your Company at all? [$ (^Ann.^) $] Yes about Ten a Clock. [$ (^Record.^) $] Woman you must be mistaken, he came to Town at Twelve or One, and might be in thy company, but it is plain he went to a Brokers in (^Long-lane^) , and so to the (^Artillery-Ground^) at (^Cripple-Gate^) , for I guess it might be so: Then they went to (^Whetstones-Park^) , and spent Six-Pence, and after that they went into (^Drury-lane^). [$ (^Giles,^) $] My Lord, she don't say she was with us all the while, but we came to an House where she was, and several other People our Neighbours.


Some important findings

Historical courtroom discourse is not just made up of questions and answers (even during examination sequences)

The frequency with which questions – and directives - were used, the function that they served, and their ability to achieve their social and/or interactional goal depended (in large part) on a number of socio-pragmatic factors:

type and date of trial position in discourse role of user & addressee ultimate aim of interaction

1640-1760 was a period of emerging and changing roles

Now beginning to explore the nineteenth century, i.e. period in which the courtroom adopted advocacy in its modern form (Cairns 1998) Utilising full trials: emerging need to consider opening/closing

statements


Linguistic theory

Natural language processing &

Computational linguistics

Corpus Empirical evidence to inform theoryStatistical and rule-

based language models

Corpus Linguistics

Historical theory

Historical theory

Historical text mining (HTM)

HTM

3. Over to you …


What research questions would you like to answer, but can’t?

Search engines for new text collections and digital libraries

Named entity extraction for GISVariant spellingsHistorical text miningNew research methods in History

Download - Corpus annotation and retrieval: an introduction Paul Rayson Computing Department, Lancaster University Dawn Archer School of Humanities, University of

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