Inferring temporal ordering of events in news
Inderjeet Mani,Barry Schiffman,Jianping Zhang +2 more
- pp 55-57
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TLDR
This paper describes a domain-independent, machine-learning based approach to temporally anchoring and ordering events in news that achieves 84.6% accuracy in temporally Anchoring events and 75.4% in partially ordering them.Abstract:
This paper describes a domain-independent, machine-learning based approach to temporally anchoring and ordering events in news. The approach achieves 84.6% accuracy in temporally anchoring events and 75.4% accuracy in partially ordering them.read more
Citations
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Machine Learning of Temporal Relations
TL;DR: This paper used temporal reasoning as an over-sampling method to dramatically expand the amount of training data, resulting in predictive accuracy on link labeling as high as 93% using a Maximum Entropy classifier on human annotated data.
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Learning causality for news events prediction
TL;DR: A new methodology for modeling and predicting such future news events using machine learning and data mining techniques is presented, and the Pundit algorithm generalizes examples of causality pairs to infer a causality predictor.
Proceedings ArticleDOI
Automating Temporal Annotation with TARSQI
Marc Verhagen,Inderjeet Mani,Roser Saurí,Jessica Littman,Robert Knippen,Seok B. Jang,Anna Rumshisky,John Phillips,James Pustejovsky +8 more
TL;DR: An overview of TARSQI, a modular system for automatic temporal annotation that adds time expressions, events and temporal relations to news texts, is presented.
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Temporal information extraction
Xiao Ling,Daniel S. Weld +1 more
TL;DR: TIE is presented, a novel, information-extraction system, which distills facts from text while inducing as much temporal information as possible, and performs global inference, enforcing transitivity to bound the start and ending times for each event.
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Temporal and Event Information In Natural Language Text
TL;DR: A language is presented, TimeML, which attempts to capture the richness of temporal and event related information in language, while demonstrating how it can play an important part in the development of more robust question answering systems.
References
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Journal ArticleDOI
Temporal interpretation, discourse relations and commonsense entailment
Alex Lascarides,Nicholas Asher +1 more
TL;DR: In this paper, a formal account of how to determine the discourse relations between propositions introduced in a text and the relations between the events they describe is presented, and the distinct natural interpretations of texts with similar syntax are explained in terms of defeasible rules.
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 ArticleDOI
Assigning time-stamps to event-clauses
Elena Filatova,Eduard Hovy +1 more
TL;DR: In this paper, a procedure for arranging into a time-line the contents of news stories describing the development of some situation is described, and the parts of the system that deal with 1. breaking sentences into event-clauses and 2. resolving both explicit and implicit temporal references.
The Tenses of Verbs.
TL;DR: A particularly important form of token-reflexive symbol is found in the tenses of verbs, which determine time with reference to the time point of the act of speech, i.e., of the token uttered.