Open Access
A Multilingual Approach to Annotating and Extracting Temporal Information.
George Wilson,Inderjeet Mani,Beth Sundheim,Lisa Ferro +3 more
- pp 505-512
TLDR
In this paper, a set of guidelines for annotating time expressions with a canonicalized representation of the times they refer to, and methods for extracting such time expressions from multiple languages are described.Abstract:
This paper introduces a set of guidelines for annotating time expressions with a canonicalized representation of the times they refer to, and describes methods for extracting such time expressions from multiple languages.read more
Citations
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Proceedings ArticleDOI
Inducing Temporal Graphs
TL;DR: This work considers the problem of constructing a directed acyclic graph that encodes temporal relations found in a text and achieves 83% F-measure in temporal segmentation and 84% accuracy in inferring temporal relations between two segments.
Journal ArticleDOI
Learning sentence-internal temporal relations
Mirella Lapata,Alex Lascarides +1 more
TL;DR: This paper uses a model trained on noisy and approximate data to predict intra-sentential relations present in TimeBank, a corpus annotated rich temporal information and assesses whether the proposed approach holds promise for the semi-automatic creation of temporal annotations.
Journal ArticleDOI
New challenges for text mining: mapping between text and manually curated pathways.
Kanae Oda,Jin-Dong Kim,Tomoko Ohta,Daisuke Okanohara,Takuya Matsuzaki,Yuka Tateisi,Jun'ichi Tsujii,Jun'ichi Tsujii +7 more
TL;DR: New resources are constructed to link the text with a model pathway and their detailed analysis are addressed, addressing the untapped resource, ‘bio-inference,’ as well as the differences between text and pathway representation.
Proceedings Article
Inferring Sentence-internal Temporal Relations
Mirella Lapata,Alex Lascarides +1 more
TL;DR: This paper proposes a data intensive approach for inferring sentence-internal temporal relations, which relies on a simple probabilistic model and assumes no manual coding, and explores various combinations of features.
Proceedings Article
Finding Temporal Order in Discharge Summaries
TL;DR: A robust corpus-based approach for temporal analysis of medical discharge summaries in terms of temporal segments and their ordering based on a range of linguistic and contextual features integrated in a supervised machine-learning framework.
References
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Proceedings ArticleDOI
Robust temporal processing of news
Inderjeet Mani,George Wilson +1 more
TL;DR: An annotation scheme for temporal expressions, and a method for resolving temporal expressions in print and broadcast news, based on both hand-crafted and machine-learnt rules are described.
Proceedings Article
Annotating Events and Temporal Information in Newswire Texts.
Andrea Setzer,Robert Gaizauskas +1 more
TL;DR: An annotation scheme for annotating those features and relations in texts which enable us to determine the relative order and, if possible, the absolute time, of the events reported in them is devised.
Proceedings ArticleDOI
Insights into the Dialogue Processing of VERBMOBIL
TL;DR: The dialogue module of the speech-to-speech translation system VERBMOBIL is presented, following the approach that the solution to dialogue processing in a mediating scenario can not depend on a single constrained processing tool, but on a combination of several simple, efficient, and robust components.
Proceedings ArticleDOI
Natural Language Dialogue Service for Appointment Scheduling Agents
TL;DR: COSMA is described, a fully implemented German language server for existing appointment scheduling agent systems that can cope with multiple dialogues in parallel, and accounts for differences in dialogue behaviour between human and machine agents.