Year: 2018
Type: preprint
Abstract: In this paper, we present a new corpus of entailment problems. This corpus combines the following characteristics: 1. it is precise (does not leave out implicit hypotheses) 2. it is based on "real-world" texts (i.e. most of the premises were written for purposes other than testing textual entailment). 3. its size is 150. The corpus was constructed by taking problems from the Real Text Entailment and discovering missing hypotheses using a crowd of experts. We believe that this corpus constitutes a first step towards wide-coverage testing of precise natural-language inference systems.
Source: arXiv (Cornell University)
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2904890771