Making useful wordlists for ELT Topical vocabulary from the WWW Simon Smith & Scott Sommers Ming Chuan University, Taipei Adam Kilgarriff, Lexical Computing.

Making useful wordlists for ELTTopical vocabulary from the WWW

Simon Smith & Scott SommersMing Chuan University, Taipei

Adam Kilgarriff, Lexical Computing Ltd, UK

Generous support from National Science Council, Taiwan

Outline

• Importance of learning natural English• Wordlists in English learning• Making relevant wordlists• Using two corpus analysis tools

– WebBootCat – Sketch Engine

• Conclusions and future plans

The problem

• Learning non-authentic English– It’s raining cats and dogs!– Long time no see!

• In Taiwan, all students learn these• They may believe they are authentic• But English speakers hardly use them!

Word and phrase lists

• Students must learn vocabulary• It is best to learn vocabulary through practice:

– Reading– Speaking to American people– Interacting in the language

• That is difficult for Asian students• In Taiwan, students must learn vocabulary

from lists

From the MOE

• 6000 word high school list– Probably useful for

policy makers– May be useful for

teachers– Not useful for learners

• Better to organize wordlists by topic?

So, we should teach vocabulary by topic?

Khmer learning Game © North Illinois University

Unit 1

Getting started at University

Nounsattendance course facilities helmetinitiative major vendor Verbsaccomplish consider improve tease Adjectiveschallenging fortunateimpatient occasional protective

From the ELC textbook

• It is not easy to make up a good vocabulary list for an abstract topic

• Try these topics:– Unit 1: Getting started at University– Unit 2: Family and Hometown– Unit 3: English and You

• Please– Choose a topic– Write down some good keywords

• Better use computer to help us!

Getting wordlists from the web

WebBootCat: making corpora from the web

• User chooses some seed words– For example freshman and university

• WebBootCat – searches Yahoo for seed words– throws away lists of numbers, HTML, prices lists…– puts all running text into a corpus– tags the corpus (noun, verb etc) if required

12345 56789 $$$$$ £££££*&%^

WebBootCat passes query to Yahoo!

WebBootCat throws away non-data web pages

WebBootCat puts text pages in corpus

User enters seed words

Now, we can use Sketch Engine software to make a concordance

Or, we can make a wordlist, using WebBootCat

Now, we can bootstrap a new wordlist. We use the first wordlist as seed words for the second one.

Now, let’s make a list of multi-word terms.

Advantages of automatic wordlist creation

• contain relevant, topical vocabulary

• created easily and conveniently

• of course, we can select the words manually, from the automatic list!

Disadvantages of manual wordlist creation

• It is difficult to get inspiration to make good wordlists manually.

• Manual wordlists may include rare or unnecessary vocabulary.

Future work: Automatic cloze exercise generation

Q: It’s a ___ day today!

(b) tepid(a) toasty Choose:

(c) lukewarm

(d) sunny

Summary: making wordlists

• choose a topic • get a topic corpus from the web• extract topic wordlist from it• Use recursive bootstrapping to extend the

wordlist• include multi-word terms in the wordlist

Thank you

www.sketchengine.co.uk