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AbstractOwing in part to the surge of interest in temporal relation extraction, a number of datasets manually annotated with temporal relations between event-event pairs and event-time pairs have been produced …...

Temporal evidence classification, i.e., finding associations between temporal expressions and re- lations expressed in text, is an important part of temporal relation extraction. To capture the variations found in this …...

Building unified timelines from a collection of written news articles requires cross-document event coreference resolution and temporal re- lation extraction. In this paper we present an approach event coreference resolution …...

This paper describes the outcomes of the TimeLine task (Cross-Document Event Order- ing), that was organised within the Time and Space track of SemEval-2015. Given a set of documents and …...

AbstractWe present CATENA, a sieve-based system to perform temporal and causal relation extraction and classification from English texts, exploiting the interaction between the temporal and the causal model. We evaluate …...

AbstractPrevious studies on temporal relation extraction focus on mining sentence-level information or enforcing coherence on different temporal relation types among various event mentions in the same sentence or neighboring sentences, …...

AbstractExtracting temporal relations (before, after, overlapping, etc.) is a key aspect of understanding events described in natural language. We argue that this task would gain from the availability of a …...

AbstractUnsupervised pre-trained word embeddings are used effectively for many tasks in natural language processing to leverage unlabeled textual data. Often these embeddings are either used as initializations or as fixed …...

AbstractUnderstanding natural language involves recognizing how multiple event mentions structurally and temporally interact with each other. In this process, one can induce event complexes that organize multi-granular events with temporal …...

Recently, quite a few studies have been progressive for temporal relation extraction, which is an important work used in sev- eral natural language processing applications. However, less concentration has been …...

AbstractMost previous work on temporal relation extraction only focused on extracting the temporal relations among events or suffered from the issue of different expressions of events, timexes and Document Creation …...

AbstractTemporal relation extraction aims to extract temporal relations between event pairs, which is crucial for natural language understanding. Few efforts have been devoted to capturing the global features. In this …...

AbstractExisting models to extract temporal relations between events lack a principled method to incorporate external knowledge. In this study, we introduce Bayesian-Trans, a Bayesian learning-based method that models the temporal …...