Abstract
Shared Task 1 of SemEval-2014 comprised two subtasks on the same dataset of sentence pairs: recognizing textual entailment and determining textual similarity. We used an existing system based on formal semantics and logical inference to participate in the first subtask, reaching an accuracy of 82%, ranking in the top 5 of more than twenty participating systems. For determining semantic similarity we took a supervised approach using a variety of features, the majority of which was produced by our system for recognizing textual entailment. In this subtask our system achieved a mean squared error of 0.322, the best of all participating systems.
Cite
CITATION STYLE
Bjerva, J., Bos, J., van der Goot, R., & Nissim, M. (2014). The Meaning Factory: Formal Semantics for Recognizing Textual Entailment and Determining Semantic Similarity. In 8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings (pp. 642–646). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/s14-2114
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