By Harry Bunt, Reinhard Muskens
This booklet offers an in-depth view of the present concerns, difficulties and ways within the computation of that means as expressed in language. geared toward linguists, machine scientists, and logicians with an curiosity within the computation of which means, this e-book specializes in major subject matters in fresh examine in computational semantics. the 1st subject is the definition and use of underspecified semantic representations, i.e. formal buildings that symbolize a part of the which means of a linguistic item whereas leaving different elements unspecified. the second one subject mentioned is semantic annotation. Annotated corpora became an integral source either for linguists and for builders of language and speech expertise, in particular while utilized in mixture with desktop studying tools. The annotation in corpora has merely marginally addressed semantic info, notwithstanding, in view that semantic annotation methodologies are nonetheless of their infancy. This publication discusses the advance and alertness of such methodologies.
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Extra resources for Computing Meaning: Volume 3
04%) generated are associated with a QLF by the f-structure–QLF translation algorithm. 76% (46371) of the 48424 trees in the Penn treebank receive a QLF. DERIVING QUASI-LOGICAL FORMS 47 6. A Tree De-Transformation Approach It is interesting to compare our work with (Liakata and Pulman, 2002). Liakata and Pulman translate Penn-II treebank trees into ﬂat, setbased descriptions much like (Frank, 2000) and then match these descriptions with templates to extract logical forms. In order to cope with passive and non-local (“moved”) material, they pre-process the (ﬂat representations of the) treebank trees to undo the eﬀects of movement: fronted (topicalised) material is moved back to the location of its coindexed empty node in the tree, passives are transformed into essentially their active counterparts etc.
Are of the form q(Ty:Var,Pred:Var). ,Argn ) where Argi are terms or forms. e. Scope as provided by the full QLF formalism. ) is treated via relational md(x,y) (modiﬁer) or eq(x,y) (equality) predicates linking modiﬁers with referential arguments. We do not currently use the higher-order lambda abstraction nor any of the contextual resolution facilities provided by the full QLF formalism. The f-structure to QLF translation algorithm is based on (van Genabith and Crouch, 1996) and extended to include passive constructions, wh-questions, relative clauses, fronted material and subjects of participal clauses, gerunds and inﬁnitival clauses, modiﬁcation (adjectival, adverbial, prepositional, appositional and sentential and non-sentential adjuncts as well as relative clauses) and coordinate/subordinate constructions.
Uk/~fracas/. Webber, B. : 1991, ‘Structure and Ostension in the Interpretation of Discourse Deixis’. Language and Cognitive Processes 6(2), 107–135. Zwicky, A. and J. Sadock: 1975, ‘Ambiguity Tests and How to Fail Them’. In: J. ): Syntax and Semantics 4. New York: Academic Press, pp. 1–36. AOIFE CAHILL, MAIREAD MCCARTHY, MICHAEL BURKE, JOSEF VAN GENABITH AND ANDY WAY DERIVING QUASI-LOGICAL FORMS FROM F-STRUCTURES FOR THE PENN TREEBANK 1. Introduction Probabilistic parsers and grammars extracted from treebanks (cf.