Semantic Annotation - VISL

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<strong>Semantic</strong> prototypes vs. Wordnet ● ● ● only ISA, no meronyms/holonyms/antonyms linguistic vs. encyclopaedic (dolphin, penguin) shallow vs. deep ontology, distinctional vs. definitiona . cavalo -- (Animals, Biology) -> equídeos -- (Animals, Biology) -> perissodáctilos -- (Animals, Biology) -> ungulados -- (Animals, Biology) -> eutérios, placentários -- (Animals, Biology) -> mamíferos -- (Animals, Biology) -> vertebrado -- (Animals, Biology) -> cordados -- (Animals, Biology) -> animal, bicho -- (Animals, Biology) -> criatura, organismo, ser, ser_vivo -- (Biology) -> coisa, entidade -- (Factotum)
<strong>Semantic</strong> prototypes vs. Wordnet 2 ● ● ● ● tagger/parser-friendly: ideally 1 sem tag, like PoS etc. ideally, not more finegrained than what can be disambiguated by linguistic context – major classes should allow formal tests or feature contrasting – e.g. ±HUM, ±MOVE, type of preposition (“durante”, “em”), ±CONTROL, test-verbs (comer, beber, dizer, produzir) careful with “metaphor polysemy explosion” – NOT inspired by classical dictionaries systematic relations between classes may be left underspecified, e.g. --> , --> , --> , -->
Page 1 and 2: Semantic Annotation Eckhard Bick In
Page 3 and 4: Why higher-level Annotation ● ●
Page 5 and 6: The annotation method ● ● Infor
Page 7 and 8: what is a semantic prototype ●
Page 12 and 13: Lexico-semantic tags in Constraint
Page 14 and 15: PALAVRAS Semantic prototypes ●
Page 16 and 17: feature inheritance
Page 18 and 19: prototypes or atomic features ● R
Page 20 and 21: Why valency has a semantic dimensio
Page 22 and 23: Semantic role annotation for Portug
Page 24 and 25: "Nominal" The semantic role invento
Page 26 and 27: "Syntactic definition example roles
Page 28 and 29: Dependency trees will organize orga
Page 30 and 31: Inferring semantic roles from verb
Page 32 and 33: ● ● ● ● ● ● ● ● Age
Page 34 and 35: Grammar profile ● ● ● ● Abo
Page 36 and 37: Semantic role tagging performance o
Page 38 and 39: ● ● ● ● ● smallest syntac
Page 40 and 41: Portuguese parser: beta.visl.sdu.dk
Page 42 and 43: A usage example: Using “deeply”
Page 44 and 45: aw text: - Wikipedia - newspaper -
Page 49: DeepDict: explicit semantics (seman

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