Abstract
Natural language inference (NLI) is a key part of natural language understanding. The NLI task is defined as a decision problem whether a given sentence – hypothesis – can be inferred from a given text. Typically, we deal with a text consisting of just a single premise/single sentence, which is called a single premise entailment (SPE) task. Recently, a derived task of NLI from multiple premises (MPE) was introduced together with the first annotated corpus and corresponding several strong baselines. Nevertheless, the further development in MPE field requires accessibility of huge amounts of annotated data. In this paper we introduce a novel method for rapid deriving of MPE corpora from an existing NLI (SPE) annotated data that does not require any additional annotation work. This proposed approach is based on using an open information extraction system. We demonstrate the application of the method on a well known SNLI corpus. Over the obtained corpus, we provide the first evaluations as well as we state a strong baseline.- Anthology ID:
- R19-1144
- Volume:
- Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
- Month:
- September
- Year:
- 2019
- Address:
- Varna, Bulgaria
- Editors:
- Ruslan Mitkov, Galia Angelova
- Venue:
- RANLP
- SIG:
- Publisher:
- INCOMA Ltd.
- Note:
- Pages:
- 1257–1264
- Language:
- URL:
- https://aclanthology.org/R19-1144
- DOI:
- 10.26615/978-954-452-056-4_144
- Cite (ACL):
- Martin Víta and Jakub Klímek. 2019. Exploiting Open IE for Deriving Multiple Premises Entailment Corpus. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 1257–1264, Varna, Bulgaria. INCOMA Ltd..
- Cite (Informal):
- Exploiting Open IE for Deriving Multiple Premises Entailment Corpus (Víta & Klímek, RANLP 2019)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/R19-1144.pdf