metadata

dataset_info:
  - config_name: papyrus-a
    features:
      - name: doc_id
        dtype: int64
      - name: title
        dtype: string
      - name: input_text
        dtype: string
      - name: keyphrases
        sequence: string
      - name: lang
        dtype: string
    splits:
      - name: train
        num_bytes: 48856197
        num_examples: 11290
      - name: test
        num_bytes: 14237516
        num_examples: 3261
      - name: validation
        num_bytes: 7101302
        num_examples: 1638
    download_size: 39852407
    dataset_size: 70195015
  - config_name: papyrus-e
    features:
      - name: doc_id
        dtype: int64
      - name: title
        dtype: string
      - name: input_text
        dtype: string
      - name: keyphrases
        sequence: string
      - name: lang
        dtype: string
    splits:
      - name: train
        num_bytes: 23220234
        num_examples: 10508
      - name: test
        num_bytes: 6777041
        num_examples: 3046
      - name: validation
        num_bytes: 3394239
        num_examples: 1539
    download_size: 19090105
    dataset_size: 33391514
  - config_name: papyrus-f
    features:
      - name: doc_id
        dtype: int64
      - name: title
        dtype: string
      - name: input_text
        dtype: string
      - name: keyphrases
        sequence: string
      - name: lang
        dtype: string
    splits:
      - name: train
        num_bytes: 26332755
        num_examples: 10299
      - name: test
        num_bytes: 7691101
        num_examples: 2981
      - name: validation
        num_bytes: 3820763
        num_examples: 1488
    download_size: 20986924
    dataset_size: 37844619
  - config_name: papyrus-m
    features:
      - name: doc_id
        dtype: int64
      - name: title
        dtype: string
      - name: input_text
        dtype: string
      - name: keyphrases
        sequence: string
      - name: lang
        dtype: string
    splits:
      - name: train
        num_bytes: 49906922
        num_examples: 20963
      - name: test
        num_bytes: 14543415
        num_examples: 6061
      - name: validation
        num_bytes: 7242231
        num_examples: 3040
    download_size: 40019743
    dataset_size: 71692568
configs:
  - config_name: papyrus-a
    data_files:
      - split: train
        path: papyrus-a/train-*
      - split: test
        path: papyrus-a/test-*
      - split: validation
        path: papyrus-a/validation-*
  - config_name: papyrus-e
    data_files:
      - split: train
        path: papyrus-e/train-*
      - split: test
        path: papyrus-e/test-*
      - split: validation
        path: papyrus-e/validation-*
  - config_name: papyrus-f
    data_files:
      - split: train
        path: papyrus-f/train-*
      - split: test
        path: papyrus-f/test-*
      - split: validation
        path: papyrus-f/validation-*
  - config_name: papyrus-m
    data_files:
      - split: train
        path: papyrus-m/train-*
      - split: test
        path: papyrus-m/test-*
      - split: validation
        path: papyrus-m/validation-*
license: apache-2.0
language:
  - en
  - fr
tags:
  - text-to-text
  - keyphrase-generation
pretty_name: Papyrus
size_categories:
  - 10K<n<100K

Dataset Card for Papyrus

Paper: A new dataset for multilingual keyphrase generation
Github: https://github.com/smolPixel/French-keyphrase-generation

Dataset Description

Dataset Summary

The datasets are derived from Papyrus, a repository at Université de Montréal containing various types of documents, mainly theses with abstracts in multiple languages, primarily French and English. The entries are provided in four different configurations based on the languages of abstracts, allowing for generating keyphrases in French, English, or multiple languages.

Papyrus-f: From the French abstracts, generate French keyphrases.
Papyrus-e: From the English abstracts, generate English keyphrases.
Papyrus-m: From one abstract in any language, generate keyphrases in that same language (one language to one language).
Papyrus-a: From the multiple abstracts of a document, generate keyphrases in the same languages as the abstracts (many to many languages).

Languages

Main languages: English, French
Others: Spanish, German, Italian, Portuguese, Arabic, Tagalog, Catalan, Greek, Turkish, Russian, Polish, Farsi, Indonesian, Lingala, Swedish, Finnish, Romanian, Korean

Dataset Structure

Dataset content

Config	Train set size	Valid. set size	Test set size
papyrus-m	20963	3040	6061
papyrus-e	10508	1539	3046
papyrus-f	10299	1488	2981
papyrus-a	11290	1638	3261

Data fields

doc_id: a unique id for the original document.
title: title of the thesis or article (the language of the title does not always match the language of the abstract/keyphrases).
input_text: abstract of the document.
keyphrases: associated keyphrases.
lang: language of the abstract/keyphrases.

Citation

@inproceedings{NEURIPS2022_f8870955,
    author = {Piedboeuf, Fr\'{e}d\'{e}ric and Langlais, Philippe},
    booktitle = {Advances in Neural Information Processing Systems},
    editor = {S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh},
    pages = {38046--38059},
    publisher = {Curran Associates, Inc.},
    title = {A new dataset for multilingual keyphrase generation},
    url = {https://proceedings.neurips.cc/paper_files/paper/2022/file/f88709551258331f9ab31b33c71021a4-Paper-Datasets_and_Benchmarks.pdf},
    volume = {35},
    year = {2022}
}