An algorithm for functional uncertainty

Kaplan, Ronald M.; Maxwell, John T.

doi:10.3115/991635.991695

Cited by 42 publications

(32 citation statements)

References 3 publications

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“…Kaplan & Zaenen (1989) and Kaplan & Maxwell (1988) proposed that a long-distance-antecedent is linked directly with the functional structure of a predicate. The functional or f-structure level of LFG is defined in terms of grammatical relations like TOPIC, OBJ, and COMP.…”

Section: Valence-and Gap-filling Formalismsmentioning

confidence: 99%

An On-Line Computational Model of Human Sentence Interpretation: A Theory of the Representation and Use of Linguistic Knowledge

Jurafsky¹

1992

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This dissertation presents a model of the human sentence interpretation process, which attempts to meet criteria of adequacy imposed by the different paradigms of sentence interpretation. These include the need to produce a high-level interpretation, to embed a linguistically motivated grammar, and to be compatible with psycholinguistic results on sentence processing.The model includes a theory of grammar called Construction-Based Interpretive Grammar (CIG) and an interpreter which uses the grammar to build an interpretation for single sentences. An implementation of the interpreter has been built called Sal.Sal is an on-line interpreter, reading words one at a time and updating a partial interpretation of the sentence after each constituent. This constituent-by-constituent interpretation is more finegrained and hence more on-line than most previous models. Sal is strongly interactionist in using both bottom-up and top-down knowledge in an evidential manner to access a set of constructions to build interpretations. It uses a coherence-based selection mechanism to choose among these candidate interpretations, and allows temporary limited parallelism to handle local ambiguities. Sal's architecture is consistent with a large number of psycholinguistic results.The interpreter embodies a number of strong claims about sentence processing. One claim is uniformity, with respect to both representation and process. In the grammar, a single kind of knowledge structure, the grammatical construction, is used to represent lexical, syntactic, idiomatic, and semantic knowledge. CIG thus does not distinguish between the lexicon, the idiom dictionary, the syntactic rule base, and the semantic rule base. Uniformity in processing means that there is no distinction between the lexical analyzer, the parser, and the semantic interpreter. Because these kinds of knowledge are represented uniformly, they can be accessed, integrated, and disambiguated by a single mechanism.A second claim the interpreter embodies is that sentence processing is fundamentally knowledge-intensive and expectation-based. The representation and integration of constructions uses many diverse types of linguistic knowledge. Similarly, the access of constructions is sensitive to top-down and bottom-up, syntactic and semantic knowledge, and the selection of constructions is based on coherence with grammatical knowledge and the interpretation.iii Acknowledgements This dissertation would not have been possible without the support and advice of many people. First, my advisor Robert Wilensky, who has given me guidance and generous support throughout my dissertation work. He carefully read and critiqued my work, and our discussions resulted in many of the ideas presented here. The other members of my committee, Charles Fillmore, who was also my undergraduate advisor, Jerry Feldman, and Paul Kay, were extremely supportive and helpful throughout.I owe an especial debt of gratitude to Nigel Ward, Graeme Hirst, and Jane Edwards, who read every chapter, and whose comme...

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Section: Valence-and Gap-filling Formalismsmentioning

confidence: 99%

An On-Line Computational Model of Human Sentence Interpretation: A Theory of the Representation and Use of Linguistic Knowledge

Jurafsky¹

1992

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“…But the treatment of long-distance dependence appears to necessitate the use of some recursion even in the featurestructure component (cf. Zaenen 1988 andMaxwell 1988). This has justified the attempt to develop feature structure description languages which can describe both the context-free and the categorial components of language-and which therefore foresee a fairly liberal use of recursion.…”

Section: A Richer Constraint Languagementioning

confidence: 99%

“…Intuitively, SCOPE* is the kernel, or nuclear scope of a complex formula; it functions as a regular path specification of the sort used by Kaplan and Maxwell 1988. Furthermore, quantified-wff is subject to a type restriction that SCOPES* is either identical to the value of SCOPE or to the value of SCOPE* in the scope.…”

Section: Underspecified Scopesmentioning

confidence: 99%

A feature-based syntax/semantics interface

Nerbonne¹

1993

Ann Math Artif Intell

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Syntax/Semantics interfaces using unification-based or feature-based formalisms are increasingly common in the existing computational linguistics literature. The primary reason for attempting to specify a syntax/semantics interface in feature structures is that it harmonizes so well with the way in which syntax is now normally described; this close harmony means that syntactic and semantic processing (and indeed other processing, see below) can be as tightly coupled as one wishes-indeed, there need not be any fundamental distinction between them at all. In this paper, we first point out several advantages of the unification-based view of the syntax/semantics interface over standard views. These include (i) a more flexible relation to nonsyntactic constraints on semantics; (ii) a characterization of semantic ambiguity, which in turn provides a framework in which to describe disambiguation, and (iii) the opportunity to underspecify meanings in a way difficult to reconcile with other views. The last point is illustrated with an application to the notorious scope ambiguity problem.

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“…A restricted version of the problem was addressed in [ Kaplan and Maxwell, 1988 ] , where a partial solution involving an acyclicity condition is given.…”

Section: Functional Uncertaintymentioning

confidence: 99%

“…Another interesting application of the undecidability of the word problem in Thue systems is a reduction from the word problem to satisfiability of feature terms that contain functional uncertainty [ Kaplan and Maxwell, 1988 ] . This term-forming operator was invented for the concise description of so-called long-distance dependencies in lfg [ Kaplan and Bresnan, 1982 ] .…”

Section: Functional Uncertaintymentioning

confidence: 99%

Attributive description formalisms ... and the rest of the world

Nebel¹,

Smolka

1991

Text Understanding in LILOG

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Research in knowledge representation has led to the development of so-called terminological logics, the purpose of which is to support the representation of the conceptual and terminological part of Artificial Intelligence applications. Independently, in computational linguistics, so-called feature logics have been developed which are aimed at representing the semantic and syntactic information natural language sentences convey. Since both of these logics rely mainly on attributes as the primary notational primitives for representing knowledge, they can be jointly characterized as attributive description formalisms.Although the intended applications for terminological logics and feature logics are not identical, and the computational services of systems based on the respective formalisms are quite different for this reason, the logical foundations turn out to be very similar -as we pointed out elsewhere. In this paper, we will show how attributive description formalisms relate to "the rest of the world." Recently, a number of formal results in the area of attributive description formalisms have been obtained by exploiting other research fields, such as formal language theory, automata theory, and modal logics. This connection between these different fields of formal research will be highlighted in the sequel.

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An algorithm for functional uncertainty

Cited by 42 publications

References 3 publications

An On-Line Computational Model of Human Sentence Interpretation: A Theory of the Representation and Use of Linguistic Knowledge

An On-Line Computational Model of Human Sentence Interpretation: A Theory of the Representation and Use of Linguistic Knowledge

A feature-based syntax/semantics interface

Attributive description formalisms ... and the rest of the world

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