NLP/Event-Extraction
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@ -17,41 +17,96 @@ Closed-domain event extraction uses predefined event schema to discover and extr
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<a href="https://arxiv.org/pdf/2008.00364.pdf">Event trigger:the main word that most clearly expresses an event occurrence, typically a verb or a noun.</summary><blockquote><p align="justify">
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<a >Event trigger</summary><blockquote><p align="justify">
the main word that most clearly expresses an event occurrence, typically a verb or a noun.
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Event mention:a phrase or sentence describing an event, including a trigger and several arguments.
Event trigger:the main word that most clearly expresses an event occurrence, typically a verb or a noun.
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<summary/>
<a >Event argument</summary><blockquote><p align="justify">
an entity mention, temporal expression or value that serves as a participant or attribute with a specific role in an event.
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<a >Argument role</summary><blockquote><p align="justify">
the relationship between an argument to the event in which it participants.
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Event argument:an entity mention, temporal expression or value that serves as a participant or attribute with a specific role in an event.
Argument role:the relationship between an argument to the event in which it participants.
D.Ahn [the stages of event extraction] first proposed to divide the ACE event extraction task into four subtasks: trigger detection, event/trigger type identification, event argument detection, and argument role identification.
Event mention: a phrase or sentence within which an event is described, including a trigger and arguments.
<details/>
<summary/>
<a >Event mention</summary><blockquote><p align="justify">
a phrase or sentence within which an event is described, including a trigger and arguments.
</p></blockquote></details>
Event trigger: the main word that most clearly expresses the occurrence of an event (An ACE event trigger is typically a verb or a noun).
Event argument: an entity mention, temporal expression or value (e.g. Job-Title) that is involved in an event (viz., participants).
<details/>
<summary/>
<a >Event trigger</summary><blockquote><p align="justify">
the main word that most clearly expresses the occurrence of an event (An ACE event trigger is typically a verb or a noun).
</p></blockquote></details>
<details/>
<summary/>
<a >Event argument</summary><blockquote><p align="justify">
an entity mention, temporal expression or value (e.g. Job-Title) that is involved in an event (viz., participants).
</p></blockquote></details>
<details/>
<summary/>
<a >Argument role</summary><blockquote><p align="justify">
the relationship between an argument to the event in which it participates.
</p></blockquote></details>
Argument role: the relationship between an argument to the event in which it participates.
### Open domain
Without predefined event schemas, open-domain event extraction aims at detecting events from texts and in most cases, also clustering similar events via extracted event key-words. Event keywords refer to those words/phrases mostly describing an event, and sometimes keywords are further divided into triggers and arguments.
Story segmentation: detecting the boundaries of a story from news articles.
First story detection: detecting the story that discuss anew topic in the stream of news.
Topic detection: grouping the stories based on the topics they discuss.
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<a >Story segmentation</summary><blockquote><p align="justify">
detecting the boundaries of a story from news articles.
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Topic tracking: detecting stories that discuss a previously known topic.
Story link detection: deciding whether a pair of stories discuss the same topic.
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<a >First story detection</summary><blockquote><p align="justify">
detecting the story that discuss anew topic in the stream of news.
</p></blockquote></details>
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<summary/>
<a >Topic detection</summary><blockquote><p align="justify">
grouping the stories based on the topics they discuss.
</p></blockquote></details>
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<summary/>
<a >Topic tracking</summary><blockquote><p align="justify">
detecting stories that discuss a previously known topic.
</p></blockquote></details>
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<a >Story link detection</summary><blockquote><p align="justify">
deciding whether a pair of stories discuss the same topic.
</p></blockquote></details>
The first two tasks mainly focus on event detection; and the rest three tasks are for event clustering. While the relation between the five tasks is evident, each requires a distinct evaluation process and encourages different approaches to address the particular problem.