Building Conversational Interfaces

Wheatman, Martin

doi:10.1093/itnow/bwz020

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2019

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“…The most obvious analogy is with the Skills-based retail device Alexa [5], or the Behaviour Driven Development tool Cucumber [6]; however, with these comes an immediate interpretation of an utterance in JavaScript or Gherkin. The emphasis with Enguage is depth of understanding [7] because it is programmed, itself, in natural language utterances [8,9,10]. So, rather than using the syntax-to-semantic mapping of context free languages, or some implementation of a linguistics view of language, it views each utterance as a single value: an extremely large, natural number, represented in letters.…”

Section: Enguagementioning

confidence: 99%

Pronoun Disambiguation: with Application to the Winograd Schema Challenge

Wheatman¹

2019

IJNLC

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A value-based approach to Natural Language Understanding, in particular, the disambiguation of pronouns, is illustrated with a solution to a typical example from the Winograd Schema Challenge. The worked example uses a language engine, Enguage, to support the articulation of the advocation and fearing of violence. The example illustrates the indexical nature of pronouns, and how their values, their referent objects, change because they are set by contextual data. It must be noted that Enguage is not a suitable candidate for addressing the Winograd Schema Challenge as it is an interactive tool, whereas the Challenge requires a preconfigured, unattended program.

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Section: Enguagementioning

confidence: 99%

Pronoun Disambiguation: with Application to the Winograd Schema Challenge

Wheatman¹

2019

IJNLC

View full text Add to dashboard Cite

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Building Conversational Interfaces

Cited by 1 publication

References 0 publications

Pronoun Disambiguation: with Application to the Winograd Schema Challenge

Pronoun Disambiguation: with Application to the Winograd Schema Challenge

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