@article{TACL1318,
	author = {Laparra, Egoitz  and Xu, Dongfang  and Bethard, Steven },
	title = {From Characters to Time Intervals: New Paradigms for Evaluation and Neural Parsing of Time Normalizations},
	journal = {Transactions of the Association for Computational Linguistics},
	volume = {6},
	year = {2018},
	keywords = {},
	abstract = {This paper presents the first model for time normalization trained on the SCATE corpus. In the SCATE schema, time expressions are annotated as a semantic composition of time entities. This novel schema favors machine learning approaches, as it can be viewed as a semantic parsing task. In this work, we propose a character level multi-output neural network that outperforms previous state-of-the-art built on the TimeML schema. To compare predictions of systems that follow both SCATE and TimeML, we present a new scoring metric for time intervals. We also apply this new metric to carry out a comparative analysis of the annotations of both schemes in the same corpus.},
	issn = {2307-387X},
	url = {https://www.transacl.org/ojs/index.php/tacl/article/view/1318},
	pages = {343--356}
}