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Event-based text mining for biology and functional genomics.

Ananiadou S, Thompson P, Nawaz R, McNaught J, Kell DB - Brief Funct Genomics (2014)

Bottom Line: This article provides an overview of recent research into event extraction.We cover annotated corpora on which systems are trained, systems that achieve state-of-the-art performance and details of the community shared tasks that have been instrumental in increasing the quality, coverage and scalability of recent systems.Finally, several concrete applications of event extraction are covered, together with emerging directions of research.

View Article: PubMed Central - PubMed

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Annotated meta-knowledge example. The core elements of the event (i.e. the trigger for the Regulation event, and its Theme and Cause participants) have been enriched through the identification of cues that are relevant to various dimensions interpretation of the event, according to the meta-knowledge model.
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elu015-F5: Annotated meta-knowledge example. The core elements of the event (i.e. the trigger for the Regulation event, and its Theme and Cause participants) have been enriched through the identification of cues that are relevant to various dimensions interpretation of the event, according to the meta-knowledge model.

Mentions: As an example of how the model applies to an event within a specific discourse context, consider the sentence shown in Figure 5. There is a single event of type Regulation (triggered by the verb ‘activate’), which has two participants. The Cause of the event is ‘narL gene product’ and the Theme is ‘nitrate reductase operon’. The textual context of the event provides several important pieces of information about its interpretation, each of which conveyed by the presence of a specific cue word.


Event-based text mining for biology and functional genomics.

Ananiadou S, Thompson P, Nawaz R, McNaught J, Kell DB - Brief Funct Genomics (2014)

Annotated meta-knowledge example. The core elements of the event (i.e. the trigger for the Regulation event, and its Theme and Cause participants) have been enriched through the identification of cues that are relevant to various dimensions interpretation of the event, according to the meta-knowledge model.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4499874&req=5

elu015-F5: Annotated meta-knowledge example. The core elements of the event (i.e. the trigger for the Regulation event, and its Theme and Cause participants) have been enriched through the identification of cues that are relevant to various dimensions interpretation of the event, according to the meta-knowledge model.
Mentions: As an example of how the model applies to an event within a specific discourse context, consider the sentence shown in Figure 5. There is a single event of type Regulation (triggered by the verb ‘activate’), which has two participants. The Cause of the event is ‘narL gene product’ and the Theme is ‘nitrate reductase operon’. The textual context of the event provides several important pieces of information about its interpretation, each of which conveyed by the presence of a specific cue word.

Bottom Line: This article provides an overview of recent research into event extraction.We cover annotated corpora on which systems are trained, systems that achieve state-of-the-art performance and details of the community shared tasks that have been instrumental in increasing the quality, coverage and scalability of recent systems.Finally, several concrete applications of event extraction are covered, together with emerging directions of research.

View Article: PubMed Central - PubMed

No MeSH data available.