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  This dataset represents a portion of the benchmark of the MT Challenge @CALAMITA2024.
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- The dataset focuses on evaluating Language Models' understanding of a specific linguistic structure in Italian: embedded object-extracted relative clauses (ORCs).
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  The assessment involves an 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 logically inferred from the first.
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  <!-- Provide a longer summary of what this dataset is. -->
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- The dataset contains 568 pairs of sentences, where the first sentence includes the ORC and the second sentence is the declarative sentence which can be implied or not by the first.
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  The ORCs have been primarily sourced from linguistic and psycholinguistic literature, as well as from existing benchmarks designed to test language models' ability to recognize grammatically.
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  This dataset represents a portion of the benchmark of the MT Challenge @CALAMITA2024.
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+ The dataset focuses on evaluating Language Models' understanding of a specific linguistic structure in Italian: object-extracted relative clauses (ORCs).
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  The assessment involves an 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 logically inferred from the first.
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  <!-- Provide a longer summary of what this dataset is. -->
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+ The dataset contains 566 pairs of sentences, where the first sentence includes the ORC and the second sentence is the declarative sentence which can be implied or not by the first.
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  The ORCs have been primarily sourced from linguistic and psycholinguistic literature, as well as from existing benchmarks designed to test language models' ability to recognize grammatically.
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