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README.md
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size_categories:
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---
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# Dataset Card for CLASum Dataset
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## Table of Contents
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Dataset Structure](#dataset-structure)
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- [Data Fields](#data-fields)
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- [Additional Information](#additional-information)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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## Dataset Description
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- **Point of Contact:** [Vicent Ahuir](mailto:[email protected])
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### Dataset Summary
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The CLASum is built for abstractivity characterization and measurement in the summarization task. It contains 200 document-summary pairs extracted from CNN/DailyMail and XSUM datasets. Each summary has been annotated for 11 summary-related questions by 3 different annotators.
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### Data Fields
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- `id`: Sample identifier
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- `source`: Dataset of the document-summary pair
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- `source_id`: Identifier of the pair in the original dataset
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- `document`: The document to summarize
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- `summary`: A summary for the document
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- `annotator`: Identifier of the annotator
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- `A`: Answer for a question related to relevance of the information in the summary
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- `B`: Answer for a question related to amount of novel information within the summary
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- `C`: Answer for a question related to the level of abstractivity
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- `D`: Answer for a question related to the content exclusion action
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- `E`: Answer for a question related to the information melting action
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- `F`: Answer for a question related to the syntaxis alteration action
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- `G`: Answer for a question related to the synonym action
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- `H`: Answer for a question related to the generalization action
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- `I`: Answer for a question related to the specification action
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- `J`: Answer for a question related to the ccontent reordering action
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## Additional Information
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### Licensing Information
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The CLASum dataset is released under the [Apache-2.0 License](http://www.apache.org/licenses/LICENSE-2.0).
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### Citation Information
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```
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@Unpublished{Ahuir2025,
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author = {Vicent Ahuir and Lluís-F. Hurtado},
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date = {2025-10},
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title = {Beyond ``Using Their Own Words'': Abstractivity Characterization in Summarization},
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}
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```
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