Two principles of parse preference

Hobbs, Jerry R.; Bear, John

doi:10.3115/991146.991175

Cited by 32 publications

(29 citation statements)

References 15 publications

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“…Locality principles described in the literature include Right Association (Kimball, 1973), Local Association (Frazier & Fodor, 1978), Late Closure (Frazier, 1978), Final Arguments (Ford et al, 1982), and Graded Distance Effect (Schubert, 1984(Schubert, , 1986, Rule B (Wilks, Huang, & Fass, 1985), Attach Low and Parallel (Hobbs & Bear, 1990), and Recency Preference (Gibson, 1991). These models of locality fell into two classes.…”

Section: Structural Heuristicsmentioning

confidence: 99%

“…Unlike the windowing models, in these models locality does not fall out of the structure of the parser, and must be stipulated. Iterative models differ in how they define the notion of appropriate head-this may be semantically appropriate (Wilks et al, 1985;Hobbs & Bear, 1990;Whittemore et al, 1990) or syntactically appropriate (Gibson, 1991).…”

Section: Structural Heuristicsmentioning

confidence: 99%

“…In his case, adverb& can be attached to verbs or sentences, so the Recency Preference principle requires that an adverb cannot "skip" a local verb and attach to a more distant one. Wilks et al (1985) (as the Rule B algorithm of the CASSEX program), and used also by Hobbs and Bear (1990) and Whittemore et al (1990). These models choose among attachments by attempting to attach an adverbial to each possible head, starting with the most recent, and moving further left, and selecting the first one that fits semantically.…”

Section: Structural Heuristicsmentioning

confidence: 99%

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A Probabilistic Model of Lexical and Syntactic Access and Disambiguation

1996

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Section: Structural Heuristicsmentioning

confidence: 99%

Section: Structural Heuristicsmentioning

confidence: 99%

Section: Structural Heuristicsmentioning

confidence: 99%

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A Probabilistic Model of Lexical and Syntactic Access and Disambiguation

1996

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“…In addition to production features, the stochastic LFG models evaluated below used the following kinds of features, guided by the principles proposed by Hobbs and Bear (1995). Adjunct and argument features indicate adjunct and argument attachment respectively, and permit the model to capture a general argument attachment preference.…”

Section: Features In Subgsmentioning

confidence: 99%

Estimators for stochastic "Unification-Based" grammars

Johnson

Geman

Canon

et al. 1999

Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics on Computational Linguistics -

107

164

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“…PARSING PREFERENCES Many preference strategies have been proposed in the literature for guiding parsers (Hobbs and Bear (1990) present a review). There are some preferences of syntactic (i.e.…”

Section: The Incremental Parsermentioning

confidence: 99%

Incremental dependency parsing

Lombardo¹

1992

Proceedings of the 30th Annual Meeting on Association for Computational Linguistics -

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The paper introduces a dependency-based grammar and the associated parser and focusses on the problem of determinism in parsing and recovery from errors. First, it is shown how dependency-based parsing can be afforded, by taking into account the suggestions coming from other approaches, and the preference criteria for parsing are briefly addressed. Second, the issues of the interconnection between the syntactic analysis and the semantic interpretation in incremental processing are discussed and the adoption of a TMS for the recovery of the processing errors is suggested.THE BASIC PARSING ALGORITHM The parser has been devised for a system that works on the Italian language. The structure that results from the parsing process is a dependency tree, that exhibits syntactic and semantic information.The dependency structure: The structure combines the traditional view of dependency syntax with the feature terms of the unification based formalisms (Shieber 86): single attributes (like number or tense) appear inside the nodes of the tree, while complex attributes (like grammatical relations) are realized as relations between nodes. The choice of a dependency structure, which is very suitable for free word order languages (Sgall et al. 86), reflects the intuitive idea of a language with few constraints on the order of legal constructions. Actually, the flexibility of a partially configurational language like Italian (that can be considered at an intermediate level between the totally configurational languages like English and the totally inflected free-ordered Slavonic languages) can be accounted for with a relaxation of the strong constraints posed by a constituency grammar (Stock 1989) or by constraining to a certain level a dependency grammar. Cases of topicalization, like un dolce di frutta ha ordinato il maestro a cake with fruits has ordered the teacher and in general all the five permutations of the "basic" (i.e. more likely) SVO structure of the sentence are so common in Italian, that it seems much more economical to express the syntactic knowledge in terms of dependency relations.Every node in the structure is associated with a word in the sentence, in such a way that the relation between two nodes at any level is of a head&modifier type. The whole sentence has a head, namely the verb, and its roles (the subj is included) are its modifiers. Every modifier in turn has a head (a noun, which can be a proper, common or pro-noun, for participants not marked by a preposition, a preposition, or a verb, in case of subordinate sentences not preceded by a conjunction) and further modifiers.Hence the dependency tree gives an immediate representation of the thematic structure of the sentence, thus being very suitable for the semantic interpretation. Such a structure also allows the application of the rules, based on grammatical relations, that govern complex syntactic phenomena, as revealed by the extensive work on Relational Grammar.The dependency grammar is expressed declaratively via two tables, that represent th...

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Two principles of parse preference

Cited by 32 publications

References 15 publications

A Probabilistic Model of Lexical and Syntactic Access and Disambiguation

A Probabilistic Model of Lexical and Syntactic Access and Disambiguation

Estimators for stochastic "Unification-Based" grammars

Incremental dependency parsing

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