OAGSX Title Generation Dataset

 
LINDAT / CLARIAH-CZ
  Autoři
Çano, Erion
  Identifikátor
http://hdl.handle.net/11234/1-3079
 Odkaz na záznam v
https://www.aclweb.org/anthology/2020.lrec-1.823
 Datum vydání
2019-11-01
 Typ
corpus, text
 Velikost
33 files, 38.8 gb, 34408509 entries, 12.4 gb
 Jazyky
English
 Popis
OAGSX is a title generation dataset consisting of 34408509 abstracts and titles from scientific articles. The texts were lowercased and tokenized with Stanford CoreNLP tokenizer. No other preprocessing steps were applied in this release version. Dataset records (samples) are stored as JSON lines in each text file. The data is derived from OAG data collection (https://aminer.org/open-academic-graph) which was released under ODC-BY license. This data (OAGSX Title Generation Dataset) is released under CC-BY license (https://creativecommons.org/licenses/by/4.0/). If using it, please consider citing also the following paper: Çano Erion, Bojar Ondřej. Two Huge Title and Keyword Generation Corpora of Research Articles. LREC 2020, Proceedings of the the 12th International Conference on Language Resources and Evaluation, Marseille, France, May 2020.
 Nakladatel
Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
 Sponzoři

Ministerstvo školství, mládeže a tělovýchovy České republiky

Kód projektu: CZ.02.2.69/0.0/0.0/16_027/0008495

Jméno projektu: OP VVV Mezinárodní mobilita výzkumných pracovníků Univerzity Karlovy

 

European Union

Kód projektu: H2020-ICT-2018-2-825460

Jméno projektu: ELITR - European Live Translator

 Klíčová slova
Title Generation Dataset Abstractive Text Summarization Scientific Papers Corpus
 Kolekce
LINDAT / CLARIAH-CZ Data & Tools
 Ostatní verze
Zobrazit celý záznam
 

 Soubory tohoto záznamu

Licenční kategorie:
Publicly Available

Licence: Creative Commons - Attribution 4.0 International (CC BY 4.0)
Distributed under Creative Commons Attribution Required
Icon
Název
oagsx.zip
Velikost
12.45 GB
Formát
application/zip
Popis
data
MD5
f37926dece4c79b832ecaafce6ba1f28
 Stáhnout soubor  Náhled
 Náhled souboru  
  • oagsx
    • part005.txt1 GB
    • part023.txt1 GB
    • part010.txt1 GB
    • part028.txt1 GB
    • part015.txt1 GB
    • part002.txt1 GB
    • part020.txt1 GB
    • part007.txt1 GB
    • part025.txt1 GB
    • part012.txt1 GB
    • part030.txt1 GB
    • part017.txt1 GB
    • part004.txt1 GB
    • part022.txt1 GB
    • part009.txt1 GB
    • part027.txt1 GB
    • part014.txt1 GB
    • part032.txt873 MB
    • part001.txt1 GB
    • part019.txt950 MB
    • part006.txt1 GB
    • part024.txt1 GB
    • part011.txt1 GB
    • part029.txt1 GB
    • part016.txt1 GB
    • part003.txt1 GB
    • part021.txt1 GB
    • part008.txt1 GB
    • part026.txt1 GB
    • part013.txt1 GB
    • part031.txt875 MB
    • part000.txt1 GB
    • part018.txt1 GB
Icon
Název
README.txt
Velikost
1.51 KB
Formát
Textový soubor
Popis
readme (updated on 2020-06-02)
MD5
f8c484dee332fd01753a32507d07825e
 Stáhnout soubor  Náhled
 Náhled souboru   
OAGSX Title Generation Dataset
==============================

OAGSX is a title generation dataset consisting
of 34408509 abstracts and titles from scientific 
articles. The texts were lowercased and tokenized with 
Stanford CoreNLP tokenizer. No other preprocessing steps
were applied in this release version. Dataset records 
(samples) are stored as JSON lines in each text file. 

The data is derived from OAG data collection 
(https://aminer.org/open-academic-graph) which was released 
under ODC-BY license. 

This data (OAGSX Title Generation Dataset) is released under 
CC-BY license (https://creativecommons.org/licenses/by/4.0/). 


Download
--------

This dataset can be download from LINDAT/CLARIN repository
http://hdl.handle.net/11234/1-3079


Publications
------------

If using it, please cite the following paper:

Çano Erion, Bojar Ondřej. Two Huge Title and Keyword Generation Corpora of Research Articles. 
LREC 2020, Proceedings of the the 12th In . . .