The BIUTTE Research Platform for Transformation-based Textual Entailment Recognition

Asher Stern, Ido Dagan


Abstract
Recent progress in research of the Recognizing Textual Entailment (RTE) task shows a constantly-increasing level of complexity in this research field. A way to avoid having this complexity becoming a barrier for researchers, especially for new-comers in the field, is to provide a freely available RTE system with a high level of flexibility and extensibility. In this paper, we introduce our RTE system, BiuTee2, and suggest it as an effective research framework for RTE. In particular, BiuTee follows the prominent transformation-based paradigm for RTE, and offers an accessible platform for research within this approach. We describe each of BiuTee’s components and point out the mechanisms and properties which directly support adaptations and integration of new components. In addition, we describe BiuTee’s visual tracing tool, which provides notable assistance for researchers in refining and “debugging” their knowledge resources and inference components.
Anthology ID:
2014.lilt-9.2
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Linguistic Issues in Language Technology, Volume 9, 2014 - Perspectives on Semantic Representations for Textual Inference
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2014
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LILT
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CSLI Publications
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https://aclanthology.org/2014.lilt-9.2
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Cite (ACL):
Asher Stern and Ido Dagan. 2014. The BIUTTE Research Platform for Transformation-based Textual Entailment Recognition. In Linguistic Issues in Language Technology, Volume 9, 2014 - Perspectives on Semantic Representations for Textual Inference. CSLI Publications.
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The BIUTTE Research Platform for Transformation-based Textual Entailment Recognition (Stern & Dagan, LILT 2014)
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https://aclanthology.org/2014.lilt-9.2.pdf