First Steps in Recognizing Relational Entailment – Experimental Corpus and Baselines
| Authors | |
|---|---|
| Year of publication | 2019 |
| Type | Article in Proceedings |
| Conference | Human Language Technologies as a Challenge for Computer Science and Linguistics – 2019 |
| MU Faculty or unit | |
| Citation | |
| Keywords | NLI; relational entailment; textual entailment; annotated corpus |
| Description | Recently, a task of recognizing relational entailment (RRE) was introduced as a task to decide whether the meaning of a given textual $n$-tuple $t$, i. e., the semantic relationship expressed by $t$, can be inferred from a given text $T$. Since then-tuples are obtained from theopen information extraction process, this task naturally connects two NLP fields: natural language inference (NLI) and open information extraction (open IE). The task has a “practical” counterpart: checking/proving facts stored in open knowledge bases. However, no corresponding annotated corpus has been available yet as well as baselines for this task. In this paper, we present a corpus derived fromthe well known SNLI corpus and provide baselines based on LSTM architectures and state also a baseline using “hypothesis-only”-like approach. |
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