DanNet From Dictionary to Wordnet

Transcription

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 Society for Danish Language and Literature, DSL, Copenhagen

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. 5. Conclusions JA, 2 min

3 DanNet Lexical-semantic wordnet for Danish Joint project Society for Danish Language and Literature Centre for Language Technology, University of Copenhagen 4 years ( ), ~ 400,000

4 Limited resources Adapt an existing wordnet? or Reuse other lexical-semantic resources: SIMPLE-DK Den Danske Ordbog, DDO

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 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 100,000 definitions

8 Semantic description

9 Semantic description Systematic domain info concerns relation

10 Semantic description Sense definition relevant info manually extracted

11 Semantic description Hyperonym

12 Semantic description Sense relations, i.e. synonyms

13 Semantic description Collocational information

14 Semantic description Authentic example

15 Semantic description

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 2. Characteristics of the DDO 3. Building DanNet 4. Extraction of differentia info from definitons 5. Conclusions

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 3. Adjusting the hierarchical structure

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 celle-2,small room

20 Establishing synsets lære studies fag subject videnskab science informatik informatics bromatologi nutrition science samfundsfag social studies datalogi computer science

21 Establishing synsets One synset lære studies fag subject videnskab science informatik informatics bromatologi nutrition science samfundsfag social studies datalogi computer science

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 Cf. Cruse, 1991 and 2002

23 Example: Hyponymy? træ tree kirsebærtræ cherry tree birketræ birch vejtræ roadside tree

24 Example: Hyponymy? træ tree vejtræ roadside tree kirsebærtræ cherry tree birketræ birch Orthogonal Hyponymy

25

26 Building the hierarchy TOP genstand object møbel furniture siddemøbel sitting furniture stol chair

27 Building the hierarchy TOP genstand object møbel furniture indbo/bohave household effects siddemøbel sitting furniture stol chair

28 Building the hierarchy TOP genstand object møbel furniture indbo/bohave household effects siddemøbel sitting furniture 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 Semantic relations are coded manually

30 Coding relations What is done manually: No semantic info other than that of DDO Reduction of semantic info What is done automatically: Inheritance of relations from hyperonyms

31 Outline 1. Introduction 2. Characteristics of the DDO 3. Building DanNet 4. Extraction of differentia info from definitons 5. Conclusions

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 fjernsyn tv set genus expression 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

34 Extraction of telic role fjernsyn tv set genus expression 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 Telic role: VPs headed by can

35 Extraction of telic role fjernsyn tv set genus expression 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 Telic role: VPs headed by can

36 Hypothesis

37 Hypothesis 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

38 Hypothesis Corpus query VPs Find a relative all definitions clause with which genus are apparat headed by kan can specify followed the by telic der role or som (i.e. the for_purpose_of relation) followed by of kan the definiendum followed by a word ending in e

39 Results of corpus query

40 Results of corpus query query VP heads denoting telic role dictionary entries

41 Results of corpus query query VP heads denoting telic role Only 26 occurrences of this pattern but 203 dictionary entries apparat definitions

42 Why this bad coverage?

43 Why this bad coverage? 1. Definitions where the pattern contains interposed material are not captured

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 Further patterns 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

46 Further patterns head for_purpose_of 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

47 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 Further patterns head These patterns 6. GE that is specially designed for to VP-inf for_purpose_of capture 70% of the apparat definitions

48 A statistical approach

49 A statistical approach Frequency list of types in definitions with genus apparat

50 A statistical approach Frequency list of types in definitions with genus apparat compared with

51 A statistical approach Frequency list of types in definitions with genus apparat compared with frequency list of types in all definitions

52 A statistical approach Frequency list of types in definitions with genus apparat compared with frequency list of types in all definitions using a statistical test (e.g. log likelihood)

53 A statistical approach Frequency list of types in definitions with genus apparat 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 måling,gauging måler,measuring tool målinger,measurements

55 Some salient types afspille to play back afspilning play back måle,measure måling,gauging måler,measuring tool 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, måleinstrument, kalorimeter radiosonde, satellit, fartskriver

56 Automatic extraction?

57 Automatic extraction? Basically NO... Developing reliant methods is too expensive!

58 Automatic extraction? Structural and lexical properties of definitions differ considerably

59 Automatic extraction? Structural and lexical properties of definitions differ considerably Difficult to automatically extract semantic relations from definitions

60 Automatic extraction? Structural and lexical properties of definitions differ considerably Difficult to automatically extract semantic relations from definitions Concordances and lists of salient definition types may help the editor

61 Automatic extraction? Structural and lexical properties of definitions differ considerably Difficult to automatically extract semantic relations from definitions 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 2. Characteristics of the DDO 3. Building DanNet 4. Extraction of differentia info from definitons 5. Conclusions

63 Conclusion Reusing the DDO

64 Conclusion Reusing the DDO Cheap Expensive

65 Conclusion Reusing the DDO Cheap Expensive Semi-automatic exploitation of the dictionary structure hyponymy structure synonym/antonym info

66 Conclusion Reusing the DDO Cheap Expensive Semi-automatic exploitation of the dictionary structure hyponymy structure synonym/antonym info Automatic exploitation of definitions proper to find other semantic relations

67 Conclusion Reusing the DDO Cheap Expensive Semi-automatic exploitation of the dictionary structure hyponymy structure synonym/antonym info Automatic exploitation of definitions proper to find other semantic relations

68 Conclusion The DanNet approach

69 Cheap Conclusion The DanNet approach Expensive

70 Conclusion The DanNet approach Cheap Translation/expansion of existing WNs? Expensive Better coherence with other WNs Linguistic bias

71 Conclusion The DanNet approach Cheap Translation/expansion of existing WNs? Expensive Better coherence with other WNs Linguistic bias Reusing/merging language resources? More loyal to the specific language Expensive, unless based on an existing resource, i.e. a dictionary

72 Conclusion The DanNet approach Cheap Translation/expansion of existing WNs? Expensive Better coherence with other WNs Linguistic bias Reusing/merging language resources? More loyal to the specific language Expensive, unless based on an existing resource, i.e. a dictionary