DanNet From Dictionary to Wordnet

(1)

DanNet

From Dictionary

to Wordnet

Jörg Asmussen

Society for Danish Language and Literature, DSL, Copenhagen

Bolette Sandford Pedersen

Centre for Language Technology, CST, University of Copenhagen

Lars Trap-Jensen

(2)

Outline

1. Introduction LTJ, 2 min.

2. Characteristics of the DDO LTJ, 5 min.

3. Building DanNet BSP, 8 min.

4. Extraction of differentia info JA, 7 min.

(3)

DanNet

•

Lexical-semantic wordnet for Danish

•

Joint project

•

Society for Danish Language and Literature

•

Centre for Language Technology, University of Copenhagen

(4)

Limited resources

•

Adapt an existing wordnet? or

•

Reuse other lexical-semantic resources:

•

SIMPLE-DK

(5)

Outline

1. Introduction

2. Characteristics of the DDO 3. Building DanNet

4. Extraction of differentia info from definitons 5. Conclusions

(6)

Den Danske Ordbog

•

Published by DSL 2003–5

•

Corpus-based, DDOC

•

60,000 entries

•

Spelling, morphology, pronunciation, meaning, collocations,

fixed phrases, syntax, usage, word formation, etymology

(7)

Den Danske Ordbog

•

Words edited in related groups

•

Machine readable

•

Fine-grained microstructure

(8)

(9)

Systematic domain info

→ concerns relation

(10)

Sense definition

→ relevant info „manually“ extracted

(11)

Hyperonym

(12)

Sense relations, i.e. synonyms

(13)

Collocational information

(14)

Authentic example

(15)

(16)

Definitions in the DDO

Definition scheme:

•

Genus proximum – closest hyperonym:

apparat ‚technical device‘

•

Differentia specifica – distinctive feature: remaining part of the definition

(17)

Outline

1. Introduction

(18)

Building DanNet

•

Extract definitions and genus specifications

•

Include them in the DanNet tool

•

Use it for domain-wise development of data: 1. Homonymy and polysemy

2. Establishing synsets

(19)

Homonymy & polysemy

celle ‚cell‘ is genus proximum of

•

gærcelle ,yeast cell‘

•

fængselscelle ‚prison cell‘

Convert lexical expressions into concepts:

•

celle-1 ‚part of living organism‘

(20)

Establishing synsets

lære

‚studies‘ ‚subject‘fag videnskab‚science‘

informatik ‚informatics‘ bromatologi ‚nutrition science‘ samfundsfag ‚social studies‘ datalogi ‚computer science‘

(21)

Establishing synsets

lære

‚studies‘ ‚subject‘fag videnskab‚science‘

informatik ‚informatics‘ bromatologi ‚nutrition science‘ samfundsfag ‚social studies‘ datalogi ‚computer science‘ One synset

(22)

Building the hierarchy

Hyponymy is generally defined as

•

X is a Y

Taxonymy is a subtype of this:

•

X is a kind/type of Y

(23)

Example: Hyponymy?

vejtræ ‚roadside tree‘ træ ‚tree‘ kirsebærtræ ‚cherry tree‘ birketræ ‚birch‘

(24)

Example: Hyponymy?

træ ‚tree‘ kirsebærtræ ‚cherry tree‘ birketræ ‚birch‘ vejtræ ‚roadside tree‘ „Orthogonal“ Hyponymy

(25)

(26)

Building the hierarchy

stol ‚chair‘

siddemøbel ‚sitting furniture‘

møbel ‚furniture‘

genstand ‚object‘ TOP

(27)

stol ‚chair‘

(28)

stol ‚chair‘

(29)

Definition composition

•

Genus selection – a conscious process

•

Differentia:

•

No editorial specifications, i.e. no fixed definition vocabulary nor syntax

•

Consequences for DanNet:

•

Complicates computational exploitation

(30)

Coding relations

•

What is done manually:

•

No semantic info other than that of DDO

•

Reduction of semantic info

•

What is done automatically:

(31)

Outline

1. Introduction

(32)

Extraction of telic role

fjernsyn ‚tv set‘

‚box-shaped device that can receive tv signals and transform them into animated pictures on a screen and accompanying sound in the speakers of the device‘

(33)

Extraction of telic role

genus expression

(34)

Extraction of telic role

genus expression

Telic role:

(35)

Extraction of telic role

genus expression

Telic role:

(36)

(37)

‣

VPs in a relative clause which are headed by

kan ‚can‘ specify the telic role (i.e. the

for_purpose_of relation) of the definiendum

Hypothesis

(38)

‣

VPs in a relative clause which are headed by

kan ‚can‘ specify the telic role (i.e. the

for_purpose_of relation) of the definiendum

Hypothesis

Corpus query

Find all definitions with genus apparat

followed by der or som

followed by kan

(39)

(40)

Results of corpus query

query VP

heads denoting

(41)

Results of corpus query

query VP

heads denoting

telic role dictionary entries

Only 26 occurrences

of this pattern – but 203

(42)

(43)

Why this bad coverage?

1. Definitions where the pattern contains

(44)

Why this bad coverage?

1. Definitions where the pattern contains

interposed material are not captured 2. Other stuctural patterns indicating a

for_purpose_of relation than that one given in our hypothesis

(45)

1. GE that can VP-inf

2. GE that is used for to VP-inf with

3. GE for to VP-inf with/on/in

4. GE that VP-fin 5. GE for NP

6. GE that is specially designed for to VP-inf

Further patterns

(46)

Further patterns

(47)

Further patterns

head for_purpose_of

These patterns

capture 70% of the

apparat

(48)

(49)

A statistical approach

•

Frequency list of types in definitions with genus apparat

(50)

•

(51)

•

compared with

(52)

•

compared with

•

frequency list of types in all definitions

(53)

•

compared with

•

frequency list of types in all definitions

using a statistical test (e.g. log likelihood)

‣

Salient types are listed for investigation and may give hints on semantic relations

(54)

Some salient types

•

afspille ‚to play back‘

•

afspilning ‚play back‘

•

måle ,measure‘

•

måler ,measuring tool‘

•

måling ,gauging‘

(55)

Some salient types

•

afspille ‚to play back‘

•

afspilning ‚play back‘

•

måle ,measure‘

•

måler ,measuring tool‘

•

måling ,gauging‘

•

målinger ,measurements‘

grammofon,

cd-afspiller, afspiller, sequencer, diktafon

kassettespiller,

hjemmevideo, kassettebåndoptager, båndoptager

stroboskop,

måler, timer, løgnedetektor, ekkolod gasmåler,

speedometer, omdrejningstæller, benzinmåler, fotofælde_elmåler,

trykmåler, luxmeter, spirometer, gyrometer, alkometer, newtonmeter,

magnetometer, instrument, kalorimeter

måleinstrument,

(56)

(57)

Automatic extraction?

Basically NO...

Developing reliant methods is

too expensive!

(58)

Automatic extraction?

•

Structural and lexical properties of definitions differ considerably

(59)

•

‣

Difficult to automatically extract semantic relations from definitions

(60)

•

‣

Concordances and lists of salient definition types may help the editor

(61)

•

‣

Concordances and lists of salient definition types may help the editor

‣

But the DanNet editor still has to do the core job of analysing dictionary definitions

(62)

Outline

1. Introduction

(63)

Conclusion

(64)

Conclusion

Reusing the DDO

Cheap

(65)

Conclusion

Reusing the DDO

Semi-automatic exploitation of the dictionary structure

•

hyponymy structure

•

synonym/antonym info

Cheap

(66)

Conclusion

Reusing the DDO

•

hyponymy structure

•

Automatic exploitation of definitions proper to find other semantic relations

Cheap

(67)

Conclusion

Reusing the DDO

•

hyponymy structure

•

Automatic exploitation of definitions proper to find other semantic relations

Cheap

(68)

Conclusion

(69)

Conclusion

The DanNet approach

Expensive Cheap

(70)

Conclusion

The DanNet approach

Translation/expansion of existing WNs?

•

Better coherence with other WNs

•

Linguistic bias

Expensive Cheap

(71)

Conclusion

The DanNet approach

•

Linguistic bias

Reusing/merging language resources?

•

More loyal to the specific language

•

Expensive, unless based on an existing resource, i.e. a dictionary

Expensive Cheap

(72)

Conclusion

The DanNet approach

•

Linguistic bias

Reusing/merging language resources?

•

More loyal to the specific language

•

Expensive, unless based on an existing resource, i.e. a dictionary

Expensive Cheap