README.md

---
license: apache-2.0
dataset_info:
  features:
  - name: id
    dtype: int64
  - name: source
    dtype: string
  - name: source_id
    dtype: string
  - name: document
    dtype: string
  - name: summary
    dtype: string
  - name: annotator
    dtype: int64
  - name: A
    dtype: int64
  - name: B
    dtype: int64
  - name: C
    dtype: int64
  - name: D
    dtype: int64
  - name: E
    dtype: int64
  - name: F
    dtype: int64
  - name: G
    dtype: int64
  - name: H
    dtype: int64
  - name: I
    dtype: int64
  - name: J
    dtype: int64
  splits:
  - name: train
    num_bytes: 1333902
    num_examples: 600
  download_size: 289350
  dataset_size: 1333902
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
task_categories:
- summarization
language:
- en
tags:
- characterization
- abstractivity
- mesurement
pretty_name: CLASum
size_categories:
- n<1K
---

# Dataset Card for CLASum Dataset

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
- [Dataset Structure](#dataset-structure)
  - [Data Fields](#data-fields)
- [Additional Information](#additional-information)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)

## Dataset Description

- **Point of Contact:** [Vicent Ahuir](mailto:vahuir@upv.es)

### Dataset Summary

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.  

### Data Fields

- `id`: Sample identifier
- `source`: Dataset of the document-summary pair 
- `source_id`: Identifier of the pair in the original dataset
- `document`: The document to summarize
- `summary`: A summary for the document
- `annotator`: Identifier of the annotator
- `A`: Answer for a question related to relevance of the information in the summary
- `B`: Answer for a question related to amount of novel information within the summary 
- `C`: Answer for a question related to the level of abstractivity
- `D`: Answer for a question related to the content exclusion action 
- `E`: Answer for a question related to the information melting action 
- `F`: Answer for a question related to the syntaxis alteration action 
- `G`: Answer for a question related to the synonym action
- `H`: Answer for a question related to the generalization action
- `I`: Answer for a question related to the specification action 
- `J`: Answer for a question related to the ccontent reordering action 


## Additional Information

### Licensing Information

The CLASum dataset is released under the [Apache-2.0 License](http://www.apache.org/licenses/LICENSE-2.0). 

### Citation Information

```
@Unpublished{Ahuir2025,
  author = {Vicent Ahuir and Lluís-F. Hurtado},
  date   = {2025-10},
  title  = {Beyond ``Using Their Own Words'': Abstractivity Characterization in Summarization},
}
```