Fine-grained Entailment: Resources for Greek NLI and Precise Entailment
Paper in proceeding, 2022
In this paper, we present a number of fine-grained resources for Natural Language Inference (NLI). In particular, we present a number of resources and validation methods for Greek NLI and a resource for precise NLI. First, we extend the Greek version of the FraCaS test suite to include examples where the inference is directly linked to the syntactic/morphological properties of Greek. The new resource contains an additional 428 examples, making it in total a dataset of 774 examples. Expert annotators have been used in order to create the additional resource, while extensive validation of the original Greek version of the FraCaS by non-expert and expert subjects is performed. Next, we continue the work initiated by (CITATION), according to which a subset of the RTE problems have been labeled for missing hypotheses and we present a dataset an order of magnitude larger, annotating the whole SuperGlUE/RTE dataset with missing hypotheses. Lastly, we provide a de-dropped version of the Greek XNLI dataset, where the pronouns that are missing due to the pro-drop nature of the language are inserted. We then run some models to see the effect of that insertion and report the results.
Author
Erini Amanaki
University of Crete
Jean-Philippe Bernardy
University of Gothenburg
Chalmers, Computer Science and Engineering (Chalmers), Computing Science
Stergios Chatzikyriakidis
University of Crete
Robin Cooper
University of Gothenburg
Simon Dobnik
University of Gothenburg
Aram Karimi
University of Gothenburg
Adam Ek
University of Gothenburg
Eirini Chrysovalantou Giannikouri
University of Crete
Vasiliki Katsouli
University of Crete
Ilias Kolokousis
University of Crete
Eirini Chrysovalantou Mamatzaki
University of Crete
Dimitrios Papadakis
University of Crete
Olga Petrova
University of Crete
Erofili Psaltaki
University of Crete
Charikleia Soupiona
University of Crete
Effrosyni Skoulataki
University of Crete
Christina Stefanidou
University of Crete
Proceedings of the Workshop on Dataset Creation for Lower-Resourced Languages
44-52
978-2-493814-06-7 (ISBN)
Proceedings of the Workshop on Dataset Creation for Lower-Resourced Languages
Marseilles, France,
Marseilles, France,
Subject Categories (SSIF 2025)
Natural Language Processing
Psychology
Comparative Language Studies and Linguistics