Christina Stefanidou
2022
Fine-grained Entailment: Resources for Greek NLI and Precise Entailment
Eirini Amanaki
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Jean-Philippe Bernardy
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Stergios Chatzikyriakidis
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Robin Cooper
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Simon Dobnik
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Aram Karimi
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Adam Ek
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Eirini Chrysovalantou Giannikouri
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Vasiliki Katsouli
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Ilias Kolokousis
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Eirini Chrysovalantou Mamatzaki
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Dimitrios Papadakis
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Olga Petrova
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Erofili Psaltaki
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Charikleia Soupiona
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Effrosyni Skoulataki
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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.
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