TimeML-Compliant Text Analysis for Temporal Reasoning
Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence. Pages 997-1002.
Abstract
Reasoning with time 1 needs more than just a list of temporal expressions. T ime ML —an emerging standard for temporal annotation as a language capturing properties and relationships among timedenoting expressions and events in text—is a good starting point for bridging the gap between temporal analysis of documents and reasoning with the information derived from them. Hard as T ime MLcompliant analysis is, the small size of the only currently available annotated corpus makes it even harder. We address this problem with a hybrid T ime ML annotator, which uses cascaded finite-state grammars (for temporal expression analysis, shallow syntactic parsing, and feature generation) together with a machine learning component capable of effectively using large amounts of unannotated data.
@inproceedings{ijcai2005p142,
title = {TimeML-Compliant Text Analysis for Temporal Reasoning},
author = {Boguraev, Branimir and Ando, Rie Kubota},
booktitle = {Proceedings of the Nineteenth International Joint Conference on
Artificial Intelligence, {IJCAI-05}},
publisher = {International Joint Conferences on Artificial Intelligence},
pages = {997--1002},
year = {2005},
url = {https://ijcai.org/proceedings/2005/142},
}
TY - CPAPER TI - TimeML-Compliant Text Analysis for Temporal Reasoning AU - Boguraev, Branimir AU - Ando, Rie Kubota T2 - Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, IJCAI-05 PB - International Joint Conferences on Artificial Intelligence PY - 2005 SP - 997 EP - 1002 UR - https://ijcai.org/proceedings/2005/142 ER -Copied
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