FATE: Annotating a Textual Entailment Corpus with FrameNet

Aljoscha Burchardt, Marco Pennacchiotti

In: Nancy Ide , James Pustejovsky . Handbook of Linguistic Annotation. Seiten 1101-1118 ISBN 978-94-024-0881-2 Springer Netherlands Dordrecht 2017.


Several works show that predicate-argument structure is a level of analysis relevant for addressing Natural Language Processing problems, such as Textual Entailment (another study on Textual Entailment can be found in this volume). Although large resources like FrameNet are available (see also the chapter on FrameNet in this volume), attempts to integrate this type of information into a system for textual entailment has not delivered the expected gain in performance. The reasons for this result are not fully obvious; candidates include FrameNet's restricted coverage, limitations of semantic parsers, or insufficient modeling of FrameNet information. To enable further insight on this issue, in this paper we present FATE (FrameNet-Annotated Textual Entailment), a manually built, fully reliable frame-annotated RTE corpus. The annotation covers the 800 pairs of the RTE-2 test set. This dataset offers a safe basis for RTE systems to experiment, and enables researchers to develop clearer ideas on how to integrate frame knowledge effectively into semantic inference tasks like recognizing textual entailment. We describe and present statistics over the adopted annotation, which introduces a new schema based on full-text annotation of so called relevant frame-evoking elements. (This chapter is based on Burchardt, Pennacchiotti, Proceedings of the sixth international conference on language resources and evaluation (LREC'08) (2008) [7].)

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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence