Lexical Semantics and Knowledge Representation in Multilingual Text Generation

Stede, Manfred

doi:10.1007/978-1-4615-5179-9

Cited by 24 publications

(21 citation statements)

References 44 publications

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“…Recent work views lexical choice as the process of mapping fi'om a set of concepts (in some representation of knowledge) to a word or phrase (Elhadad, 1992;Stede, 1996). When the same concept admits more than one lexicalization, it is often difficult to choose which of these 'synonyms' is the most appropriate for achieving the desired pragmatic goals: but this is necessary for highquality machine translation and natural language generation.…”

Section: Introductionmentioning

confidence: 99%

Choosing the word most typical in context using a lexical co-occurrence network

Edmonds¹

1997

Proceedings of the 35th Annual Meeting on Association for Computational Linguistics -

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This paper presents a partial solution to a component of the problem of lexical choice: choosing the synonym most typical, or expected, in context. We apply a new statistical approach to representing the context of a word through lexical co-occurrence networks. The implementation was trained and evaluated on a large corpus, and results show that the inclusion of second-order co-occurrence relations improves the performance of our implemented lexical choice program.

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Section: Introductionmentioning

confidence: 99%

Choosing the word most typical in context using a lexical co-occurrence network

Edmonds¹

1997

Proceedings of the 35th Annual Meeting on Association for Computational Linguistics -

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“…McNamara (in press), on the other hand, does not consider using definitions or examples to be part of paraphrasing, but rather considers them elaboration. Stede (1996) considers different aspects or intentions to be paraphrases if they mention the same content or situation.…”

Section: Paraphrasementioning

confidence: 99%

“…A number of people have worked on paraphrasing such as the multilingual-translation recognition by Smith (2003), the multilingual sentence generation by Stede (1996), universal model paraphrasing using transformation by Murata and Isahara (2001), DIRT -using inference rules in question answering and information retrieval by Lin and Pantel (2001). Due to the space limitation we will mention only a few related works.…”

Section: Related Workmentioning

confidence: 99%

iSTART

Boonthum

2004

Proceedings of the ACL 2004 on Student Research Workshop -

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Paraphrase recognition is used in a number of applications such as tutoring systems, question answering systems, and information retrieval systems. The context of our research is the iSTART reading strategy trainer for science texts, which needs to understand and recognize the trainee's input and respond appropriately. This paper describes the motivation for paraphrase recognition and develops a definition of the strategy as well as a recognition model for paraphrasing. Lastly, we discuss our preliminary implementation and research plan.

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“…In the present application, we realized the linking by subordinating entities of the abstract technical model to upper model concepts. This has been mainly motivated by design decisions of the current implementation, for another more exible approach, which is motivated by w ork in lexical semantics, see Stede, 1996 . To illustrate our approach, consider the taxonomy in gure 7. It exempli es the connection between the upper model, the abstract technical model and the product speci c model for particular concepts.…”

Section: Upper Modellingmentioning

confidence: 99%

From Natural Language Documents to Sharable Product Knowledge: A Knowledge Engineering Approach

Rösner

Grote

Hartman

et al. 1998

Information Technology for Knowledge Management

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A great part of the product knowledge in manufacturing enterprises is only available in the form of natural language documents. The know-how recorded in these documents is an essential resource for successful competition in the market. From the viewpoint of knowledge management, however, documents have a severe limitation: They do not capture the wealth of knowledge contained in these documents, since the entire knowledge is not spelled out on the linguistic surface. In order to overcome this limitation, the notion of a document as a particular kind of realization of or view on the underlying knowledge is introduced. The paper discusses the major steps in realizing this approach to documents: Knowledge acquisition, knowledge representation, and techniques to automatically generate multilingual documents from knowledge bases. Further, the paper describes how the required product knowledge can be represented in a sharable and reusable way.

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Lexical Semantics and Knowledge Representation in Multilingual Text Generation

Cited by 24 publications

References 44 publications

Choosing the word most typical in context using a lexical co-occurrence network

Choosing the word most typical in context using a lexical co-occurrence network

iSTART

From Natural Language Documents to Sharable Product Knowledge: A Knowledge Engineering Approach

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