Dataset Open Access

Temporal Model XLM-RoBERTa-Base_Fullpate

Kirsanov Simon

Temporal Model "XLM-RoBERTa-Base" finetuned on the "Fullpate" dataset to solve the tasks of extraction and classification of temporal entities. Model produced in the master's thesis "Extraction and Classification of Time in Unstructured Data [Kirsanov, 2023]".

Files (764.4 MB)
Name Size
xlm-roberta-base_fullpate_multi.zip
md5:122179e4869acaed22b63d845480791c 		764.4 MB Download
Publication date:
November 1, 2023
DOI:
10.25592/uhhfdm.13633

DOI Badge

Markdown 

[![DOI](https://www.fdr.uni-hamburg.de/badge/DOI/10.25592/uhhfdm.13633.svg)](https://doi.org/10.25592/uhhfdm.13633)

reStructedText 

.. image:: https://www.fdr.uni-hamburg.de/badge/DOI/10.25592/uhhfdm.13633.svg
   :target: https://doi.org/10.25592/uhhfdm.13633

HTML 

<a href="https://doi.org/10.25592/uhhfdm.13633"><img src="https://www.fdr.uni-hamburg.de/badge/DOI/10.25592/uhhfdm.13633.svg" alt="DOI"></a>

Image URL 

https://www.fdr.uni-hamburg.de/badge/DOI/10.25592/uhhfdm.13633.svg

Target URL 

https://doi.org/10.25592/uhhfdm.13633

Keyword(s):
xlm-roberta temporal tagging temporal extraction information extraction natural language processing nlp named entity recognition ner timex3 fullpate
Communities:
License (for files):
Creative Commons Attribution 4.0 International

Versions

Version 1 10.25592/uhhfdm.13633 Nov 1, 2023
Cite all versions? You can cite all versions by using the DOI 10.25592/uhhfdm.13632. This DOI represents all versions, and will always resolve to the latest one.

Cite record as

Export