Erofili Psaltaki


2022

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Fine-grained Entailment: Resources for Greek NLI and Precise Entailment
Eirini Amanaki | Jean-Philippe Bernardy | Stergios Chatzikyriakidis | Robin Cooper | Simon Dobnik | Aram Karimi | Adam Ek | Eirini Chrysovalantou Giannikouri | Vasiliki Katsouli | Ilias Kolokousis | Eirini Chrysovalantou Mamatzaki | Dimitrios Papadakis | Olga Petrova | Erofili Psaltaki | Charikleia Soupiona | Effrosyni Skoulataki | Christina Stefanidou
Proceedings of the Workshop on Dataset Creation for Lower-Resourced Languages within the 13th Language Resources and Evaluation Conference

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.