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Structured lexicons
and Lexical semantics
Especially WordNet®
See D Jurafsky & JH Martin: Speech and Language Processing,
...
2/27
Structured lexicons
• Alternative to alphabetical dictionary
• List of words grouped according to meaning
• Classic e...
3/27
animal
bird fish ...
canary eagle trout shark
bald e. golden e. hawk e. bateleur
space
in general dimensions form mot...
4/27
Thesaurus
• A way to show the structure of (lexical)
knowledge
• Much used for technical terminology
• Can be enriche...
5/27
WordNet: History
• 1985: a group of psychologists and
linguists start to develop a “lexical
database”
– Princeton Uni...
6/27
Global organisation
• division of the lexicon into five categories:
– Nouns
– Verbs
– Adjectives
– Adverbs
– function...
7/27
Global organization
• nouns: organized as topical hierarchies
• verbs: entailment relations
• adjectives: multi-dimen...
8/27
Lexical semantics
• How are word meanings represented in WordNet?
– synsets (synonym sets) as basic units
– a word ‘m...
9/27
Synsets
• synsets often sufficient for differential
purposes
• Synsets are linked by semantic relations,
word forms a...
10/27
11/27
16.2 WORDNET: A Database of
Lexical Relations
• WordNet:
– The most well-developed and widely used
lexical DB for En...
12/27
16.2 WORDNET: A Database of
Lexical Relations
Scope of current WordNet 1.6 release in terms
of unique entries and to...
16.2 WORDNET: A Database of
Lexical Relations
A portion of the WordNet 1.6 entry for the noun bass
14/27
Lexical relations in WordNet
• WordNet is organized by semantic relations.
– It is characteristic of semantic relati...
15/27
Lexical relations
• Nouns
– Synonym ~ antonym (opposite of)
– Hypernyms (is a kind of) ~ hyponym (for example)
– Hol...
16/27
Lexical relations
Noun relations in WordNet
17/27
Lexical relations
Verb relations in WordNet
18/27
Lexical relations
Adjective and adverb relations in WordNet
19/27
WordNet’s noun hierarchy
• noun hierarchy partitioned into separate
hierarchies with unique top hypernyms
• vague ab...
20/27
• {act,action,activity}
• {animal,fauna}
• {artifact}
• {attribute,property}
• {body,corpus}
• {cognition,knowledge}...
21/27
Nouns in WordNet
• noun hierarchy as lexical inheritance
system
– seldom goes more than ten levels deep,
– the deepe...
22/27
deep
shallow
23/27
Nouns in WordNet
• man-made artefacts: sometimes six or seven
levels deep
– roadster → car → motor vehicle → wheeled...
24/27
WordNets for other languages
• Idea has been widely copied
• Sometimes by “translating” Princeton WordNet
– Lexical ...
25/27
What can WordNet be used for?
• As a lexical resource, an online dictionary,
for human use
• Word-sense disambiguati...
26/27
What can WordNet be used for?
• Document retrieval
– eg looking for texts about sports cars, search
for synonyms and...
27/27
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WORDNET: A Database of Lexical Relations

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WordNet:The most well-developed and widely used lexical DB for English.Handcrafting from scratch, rather than mining information from existing dictionaries and thesauri
Consisting three separate DBs:One each for nouns and verbs, and A third for adjectives and adverbs.

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WORDNET: A Database of Lexical Relations

  1. 1. Structured lexicons and Lexical semantics Especially WordNet® See D Jurafsky & JH Martin: Speech and Language Processing, Upper Saddle River NJ (2000): Prentice Hall, Chapter 16. and http://en.wikipedia.org/wiki/WordNet and explore WordNet: http://wordnet.princeton.edu/
  2. 2. 2/27 Structured lexicons • Alternative to alphabetical dictionary • List of words grouped according to meaning • Classic example Roget’s Thesaurus • Hierarchical organization is important • Hierarchies familiar as taxonomies, eg in natural sciences – Daughters are “types of” and share certain properties, inherited from the mother • Similar idea for ordinary words: hyponymy and synonymy
  3. 3. 3/27 animal bird fish ... canary eagle trout shark bald e. golden e. hawk e. bateleur space in general dimensions form motion size expansion distance interval contiguity reduction, deflation, shrinkage, curtailment, condensation .... hyponymy synonymy
  4. 4. 4/27 Thesaurus • A way to show the structure of (lexical) knowledge • Much used for technical terminology • Can be enriched by having other lexical relations: – Antonyms (as well as synonyms) – Different hyponymy relations, not just is-a-type-of, but has-as-part/member • Thesaurus can be explored in any direction – across, up, down – Some obvious distance metrics can be used to measure similarity between words
  5. 5. 5/27 WordNet: History • 1985: a group of psychologists and linguists start to develop a “lexical database” – Princeton University – theoretical basis: results from • WordNet organizes lexical information in terms of word meanings, rather than word forms.
  6. 6. 6/27 Global organisation • division of the lexicon into five categories: – Nouns – Verbs – Adjectives – Adverbs – function words (“probably stored separately as part of the syntactic component of language” [Miller et al.]
  7. 7. 7/27 Global organization • nouns: organized as topical hierarchies • verbs: entailment relations • adjectives: multi-dimensional hyperspaces • adverbs: multi-dimensional hyperspaces
  8. 8. 8/27 Lexical semantics • How are word meanings represented in WordNet? – synsets (synonym sets) as basic units – a word ‘meaning’ is represented by simply listing the word forms that can be used to express it • example: senses of board – a piece of lumber vs. a group of people assembled for some purpose – synsets as unambiguous designators: – {board, plank, ...} vs. {board, committee, ...} • Members of synsets are rarely true synonyms – WordNet does not attempt to capture subtle distinctions among members of the synset – may be due to specific details, or simply connotation, collocation
  9. 9. 9/27 Synsets • synsets often sufficient for differential purposes • Synsets are linked by semantic relations, word forms are linked by lexical relations.. • Preferable for cardinality of synset to be >1 – WordNet also gives a gloss for each word meaning, and (often) an example
  10. 10. 10/27
  11. 11. 11/27 16.2 WORDNET: A Database of Lexical Relations • WordNet: – The most well-developed and widely used lexical DB for English – Handcrafting from scratch, rather than mining information from existing dictionaries and thesauri – Consisting three separate DBs: • One each for nouns and verbs, and • A third for adjectives and adverbs
  12. 12. 12/27 16.2 WORDNET: A Database of Lexical Relations Scope of current WordNet 1.6 release in terms of unique entries and total numbers of senses for the four databases.
  13. 13. 16.2 WORDNET: A Database of Lexical Relations A portion of the WordNet 1.6 entry for the noun bass
  14. 14. 14/27 Lexical relations in WordNet • WordNet is organized by semantic relations. – It is characteristic of semantic relations that they are reciprocated – if there is a semantic relation R between meaning {x1, x2, ...} and meaning {y1, y2, ...}, then there is a relation R′ between {y1,y2, ...} and {x1, x2, ...} – Individual relations may or may not be • Symmetric R(A,B) ⊃ R(B,A) (eg synonymy, not hyponymy) • Transitive R(A,B) & R(B,C) ⊃ R(A,C) (eg synonymy may be) • Reflexive R(A,A) is true (synonymy is, antonymy isn’t)
  15. 15. 15/27 Lexical relations • Nouns – Synonym ~ antonym (opposite of) – Hypernyms (is a kind of) ~ hyponym (for example) – Holonym (is part of) ~ meronym (has as part) • Verbs – Synonym ~ antonym – Hypernym ~ troponym (eg lisp – talk) – Entailment (eg snore – sleep) • Adjectives/Adverbs in addition to above – Related nouns – Verb participles – Derivational information
  16. 16. 16/27 Lexical relations Noun relations in WordNet
  17. 17. 17/27 Lexical relations Verb relations in WordNet
  18. 18. 18/27 Lexical relations Adjective and adverb relations in WordNet
  19. 19. 19/27 WordNet’s noun hierarchy • noun hierarchy partitioned into separate hierarchies with unique top hypernyms • vague abstractions would be semantically empty, e.g. {entity} with immediate hyponyms {object, thing} and {idea}
  20. 20. 20/27 • {act,action,activity} • {animal,fauna} • {artifact} • {attribute,property} • {body,corpus} • {cognition,knowledge} • {communication} • {event,happening} • {feeling,emotion} • {food} • {group,collection} • {location,place} • {motive} • {natural object} • {natural phenomenon} • {person,human being} • {plant,flora} • {possession} • {process} • {quantity,amount} • {relation} • {shape} • {state,condition} • {substance} • {time}
  21. 21. 21/27 Nouns in WordNet • noun hierarchy as lexical inheritance system – seldom goes more than ten levels deep, – the deepest examples usually contain technical levels that are not part of everyday vocabulary – shallowest levels are too vague – “Inherited hypernym” option shows full hierarchy
  22. 22. 22/27 deep shallow
  23. 23. 23/27 Nouns in WordNet • man-made artefacts: sometimes six or seven levels deep – roadster → car → motor vehicle → wheeled vehicle → vehicle → conveyance → artefact • hierarchy of persons: about three or four levels – televangelist → evangelist → preacher → clergyman → spiritual leader → person • Like all thesaurus structures, words can have multiple hypernyms
  24. 24. 24/27 WordNets for other languages • Idea has been widely copied • Sometimes by “translating” Princeton WordNet – Lexical relations in general are universal ... – But are they in practice? – Are synsets universal? • EuroWordNet: combining multilingual WordNets to include cross-language equivalence – Inherent difficulties, as above
  25. 25. 25/27 What can WordNet be used for? • As a lexical resource, an online dictionary, for human use • Word-sense disambiguation (including homophone correction) – neighbouring words will be more closely related to correct sense (desert/dessert ~ camel) • Document classification – What is this text about? Look for recurring hypernyms
  26. 26. 26/27 What can WordNet be used for? • Document retrieval – eg looking for texts about sports cars, search for synonyms and hyponyms of sports car • Open-domain Q/A – Searching texts (eg WWW) to answer questions expressed in natural language – eg http://uk.ask.com/ [example] • Textual entailment – Answering questions implied by text
  27. 27. 27/27

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