Pre-trained Contextualized Character Embeddings Lead to Major Improvements in Time Normalization: a Detailed Analysis. Xu, D., Laparra, E., & Bethard, S. In Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019), pages 68–74, Minneapolis, Minnesota, 6, 2019. Association for Computational Linguistics. [Acceptance rate 33%]![Pre-trained Contextualized Character Embeddings Lead to Major Improvements in Time Normalization: a Detailed Analysis [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper bibtex @InProceedings{xu-laparra-bethard:2019:S19-1,
author = {Xu, Dongfang and Laparra, Egoitz and Bethard, Steven},
title = {Pre-trained Contextualized Character Embeddings Lead to Major Improvements in Time Normalization: a Detailed Analysis},
booktitle = {Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)},
month = {6},
year = {2019},
address = {Minneapolis, Minnesota},
publisher = {Association for Computational Linguistics},
pages = {68--74},
url = {http://www.aclweb.org/anthology/S19-1008},
note = {[Acceptance rate 33\%]},
keywords = {timelines, information extraction},
}
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