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  <!-- Provide a quick summary of the dataset. -->
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- This dataset has been proposed as part of the CALAMITA Challenge, the special event dedicated to the evaluation of Large Language Models (LLMs) in Italian and co-located with the Tenth Italian Conference on Computational Linguistics (https://clic2024.ilc.cnr.it/calamita/).
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  The dataset focuses on evaluating LLM's understanding of a specific linguistic structure in Italian: object-extracted relative clauses (ORCs).
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  The assessment involves a yes/no entailment task in which the model is given two sentences. The first contains the target structure, and the second is a simple declarative sentence whose meaning may or may not be inferred from the first, based on the syntactic relationship between the two noun phrases in the ORC.
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  - UniqueID: a numerical identifier for the entry;
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  - ID-mapping: an identifier mapping for cross-referencing according to the Condition;
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  - Source: the original reference from which sentence1 has been taken.
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- - Condition: The type of ORC occurring in Sentence1, based on the features of the two NPs involved (i.e. gender, number, animacy, distance) and, when appropriate, relative configuration (i.e. match, mismatch).
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  - Sentence1: the first sentence containing the ORC;
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  - Sentence2: the second sentence that may or may not be implied by sentence1;
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  - NP Target: indicates whether Sentence2 targets the head of the relative clause (NP1) or the subject of the embedded clause (NP2).;
 
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  <!-- Provide a quick summary of the dataset. -->
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+ TRACE-it (Testing Relative clAuses Comprehension through Entailment in ITalian) has been proposed as part of the CALAMITA Challenge, the special event dedicated to the evaluation of Large Language Models (LLMs) in Italian and co-located with the Tenth Italian Conference on Computational Linguistics (https://clic2024.ilc.cnr.it/calamita/).
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  The dataset focuses on evaluating LLM's understanding of a specific linguistic structure in Italian: object-extracted relative clauses (ORCs).
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  The assessment involves a yes/no entailment task in which the model is given two sentences. The first contains the target structure, and the second is a simple declarative sentence whose meaning may or may not be inferred from the first, based on the syntactic relationship between the two noun phrases in the ORC.
 
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  - UniqueID: a numerical identifier for the entry;
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  - ID-mapping: an identifier mapping for cross-referencing according to the Condition;
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  - Source: the original reference from which sentence1 has been taken.
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+ - Condition: The type of ORC occurring in Sentence1, based on the features of the two NPs involved (i.e. gender, number, animacy, distance) and, when appropriate, relative configuration (i.e. match, mismatch);
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  - Sentence1: the first sentence containing the ORC;
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  - Sentence2: the second sentence that may or may not be implied by sentence1;
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  - NP Target: indicates whether Sentence2 targets the head of the relative clause (NP1) or the subject of the embedded clause (NP2).;