Datasets:
File size: 3,095 Bytes
a116152 d8e5307 a116152 72ac806 a116152 d8e5307 a116152 d8e5307 a116152 d8e5307 a116152 d8e5307 a116152 d8e5307 a116152 d8e5307 a116152 d8e5307 a116152 d8e5307 a116152 d8e5307 a116152 d8e5307 a116152 72ac806 d8e5307 72ac806 a116152 adb543c d8e5307 86f7af3 17e4506 86f7af3 91ac567 86f7af3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 |
---
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 = {Ahuir, Vicent and Castro-Bleda, María José and Hurtado, Lluís-F},
date = {2025-10},
title = {Beyond Surface Metrics: Modeling Abstractivity in Summarization via Action-Based Spectrums.},
}
```
|