14,001 research outputs found
A Logic-based Approach for Recognizing Textual Entailment Supported by Ontological Background Knowledge
We present the architecture and the evaluation of a new system for
recognizing textual entailment (RTE). In RTE we want to identify automatically
the type of a logical relation between two input texts. In particular, we are
interested in proving the existence of an entailment between them. We conceive
our system as a modular environment allowing for a high-coverage syntactic and
semantic text analysis combined with logical inference. For the syntactic and
semantic analysis we combine a deep semantic analysis with a shallow one
supported by statistical models in order to increase the quality and the
accuracy of results. For RTE we use logical inference of first-order employing
model-theoretic techniques and automated reasoning tools. The inference is
supported with problem-relevant background knowledge extracted automatically
and on demand from external sources like, e.g., WordNet, YAGO, and OpenCyc, or
other, more experimental sources with, e.g., manually defined presupposition
resolutions, or with axiomatized general and common sense knowledge. The
results show that fine-grained and consistent knowledge coming from diverse
sources is a necessary condition determining the correctness and traceability
of results.Comment: 25 pages, 10 figure
Feature-based and Model-based Semantics for English, French and German Verb Phrases
This paper considers the relative merits of using features and formal event models to characterise the semantics of English, French and German verb phrases, and con- siders the application of such semantics in machine translation. The feature-based ap- proach represents the semantics in terms of feature systems, which have been widely used in computational linguistics for representing complex syntactic structures. The paper shows how a simple intuitive semantics of verb phrases may be encoded as a feature system, and how this can be used to support modular construction of au- tomatic translation systems through feature look-up tables. This is illustrated by automated translation of English into either French or German. The paper contin- ues to formalise the feature-based approach via a model-based, Montague semantics, which extends previous work on the semantics of English verb phrases. In so doing, repercussions of and to this framework in conducting a contrastive semantic study are considered. The model-based approach also promises to provide support for a more sophisticated approach to translation through logical proof; the paper indicates further work required for the fulfilment of this promise
Onebox: Free-Text Interfaces as an Alternative to Complex Web Forms
This paper investigates the problem of translating free-text\ud
queries into key-value pairs as an alternative means for searching `behind' web forms. We introduce a novel specication language for specifying free-text interfaces, and report the results of a user study where we evaluated our prototype in a travel planner scenario. Our results show that users prefer this free-text interface over the original web form and that they are about 9% faster on average at completing their search tasks
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