Semantic interpretation using KL-ONE

Sondheimer, Norman K.; Weischedel, Ralph; Bobrow, Robert

doi:10.3115/980491.980515

Cited by 23 publications

(13 citation statements)

References 9 publications

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“…The formula <p is called the prerequisite, I/A ; \\f n the justification, and x me consequent of 8 (pre (8), just (8) and cons(d) correspondingly). A default 8 is applicable to a deductively closed set of formulae E iff <pe£and -ii/rjg E, ..., ~^\^ne.…”

Section: Fly(x)mentioning

confidence: 99%

Disambiguation via Default Rules Under Answering Complex Questions

Galitsky

2005

Int. J. Artif. Intell. Tools

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Section: Fly(x)mentioning

confidence: 99%

Disambiguation via Default Rules Under Answering Complex Questions

Galitsky

2005

Int. J. Artif. Intell. Tools

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“…Q&A has a good facility to ease vocabulary acquisition from users, but it can retrieve only one file at a time. Researchers such as Sondheimer et al 22 and Hayes23 have pursued ideas on natural language understandingideas resembling our semantic interpretation using the world model. However, Sondheimer doesn't present general rules using the model like the identification rules in KID.…”

Section: Query Translationmentioning

confidence: 99%

KID Designing a Knowledge-Based Natural Language Interface

et al. 1987

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T his article presents a knowledge-based approach to designing portable natural language interfaces to database systems-an approach called KID (knowledge-based interface to database systems). To free users from needing to know about query languages and databases, and to provide users with access to databases in natural language, KID incorporates a knowledge base called the world model containing a domain model, linguistic knowledge, and database mapping knowledge. The world model is easy for users to define and understand; to transport KID to a new domain, the user has only to build a new world model for the domain. Using the world model, KID processes user queries transparently enough to enable easy user debugging of the world model. Since we have encapsulated domainspecific knowledge into the world model, KID is portable. This article will discuss world model design, and will examine KID's knowledge-based processing of queries using the world model. Numerous natural language interfaces to database systems have been developed in an attempt to make such systems more user friendly.1l2 Natural language interfaces must incorporate a knowledge base containing knowledge about a domain of discourse, databases, natural language, and a query language-thereby freeing users from needing to know about query languages and databases and enabling users to access databases in natural language. Moreover, applying natural language interfaces to new domains requires construction of new knowledge bases for those domains. Recent work focuses on portable natural language interface systems.3'4 However, no work has focused on the issues involved when users design knowledge bases by themselves to transport natural language interface systems to new domains-although one exception discusses some of these issues.5 -Gio Wiederhold Associate Editor

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“…In our model, knowledge is represented declaratively in framelike structures. In Sondheimer et al (1984), framelike structures, KL-ONE structures in fact, are also used to guide semantic interpretation in an application domain. However, other than for using framelike structures, the organization of knowledge presented here and the overall approach to the interpretation task clearly differ from those presented in that work.…”

Section: Related Researchmentioning

confidence: 99%

Determining Prepositional Attachment, Prepositional Meaning, Verb Meaning, and Thematic Roles

Gómez

Segami

Hull

1997

Computational Intelligence

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An algorithm for semantic interpretation that integrates the determination of the meaning of verbs, the attachment and meaning of prepositions, and the determination of thematic roles is presented. The parser does not resolve structural ambiguity, which is solely the task of the semantic interpreter. Lexical semantic information about nouns and verbs is applied to the resolution of verb polysemy and modifier attachment. Semantic interpretation is centered on the representation of the meaning of the verb, called verbal concept. Verbal concepts are organized into a classification hierarchy. As long as the meaning of the verb remains unknown, parsing proceeds on a syntactic basis. Once the meaning of the verb is recognized, the semantic component makes sense of the syntactic relations built so far by the parser and of those still to be parsed. The algorithm has been implemented and tested on real-world texts.

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Semantic interpretation using KL-ONE

Cited by 23 publications

References 9 publications

Disambiguation via Default Rules Under Answering Complex Questions

Disambiguation via Default Rules Under Answering Complex Questions

KID Designing a Knowledge-Based Natural Language Interface

Determining Prepositional Attachment, Prepositional Meaning, Verb Meaning, and Thematic Roles

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