KTimeML

Im, Seung-Bin; You, Hyun-Jo; Jang, Hayun; Nam, Seungho; Shin, Hyopil

doi:10.3115/1690299.1690316

Cited by 11 publications

(2 citation statements)

References 3 publications

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“…tensed and untensed verbs (e.g., was captured , to thank ), adjectives (e.g., sick ), nominals (e.g., strike ) and prepositional phrases (e.g., on board ). The consolidation of TimeML as an international standard called ISO-TimeML (ISO 2008) has facilitated its adaptation to different languages, such as Spanish (Saurí 2010) and Korean (Im et al 2009) and the release of annotated data, such as the English TimeBank (Pustejovsky et al 2003b).…”

Section: The Ie Perspective On Eventsmentioning

confidence: 99%

One, no one and one hundred thousand events: Defining and processing events in an inter-disciplinary perspective

Sprugnoli¹,

Tonelli²

2016

Nat. Lang. Eng.

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We present an overview of event definition and processing spanning 25 years of research in NLP. We first provide linguistic background to the notion of event, and then present past attempts to formalize this concept in annotation standards to foster the development of benchmarks for event extraction systems. This ranges from MUC-3 in 1991 to the Time and Space Track challenge at SemEval 2015. Besides, we shed light on other disciplines in which the notion of event plays a crucial role, with a focus on the historical domain. Our goal is to provide a comprehensive study on event definitions and investigate which potential past efforts in the NLP community may have in a different research domain. We present the results of a questionnaire, where the notion of event for historians is put in relation to the NLP perspective.

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Section: The Ie Perspective On Eventsmentioning

confidence: 99%

One, no one and one hundred thousand events: Defining and processing events in an inter-disciplinary perspective

Sprugnoli¹,

Tonelli²

2016

Nat. Lang. Eng.

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“…Interestingly, Hobbs' method of reification along with Allen's intervalbased notion of events together form the interpretive core of TimeML (Pustejovsky et al, 2003), ISO-TimeML (Pustejovsky et al, 2010), the multilingual resources built on ISO-TimeML community (Im et al, 2009;Bittar et al, 2011;Caselli et al, 2011), as well as the shared tasks based on ISO-TimeML (Verhagen et al, 2007(Verhagen et al, , 2010UzZaman et al, 2013). ISO-TimeML treats an event as a cover term for any linguistic predicate, as mentioned in a text, that happens or occurs (as with Parsons' and Allen's distinction).…”

Section: Introducing Situations and Eventsmentioning

confidence: 99%

The Role of Event-Based Representations and Reasoning in Language

2021

Computational Analysis of Storylines

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This chapter briefly reviews the research conducted on the representation of events, from the perspectives of natural language processing, artificial intelligence (AI), and linguistics. AI approaches to modeling change have traditionally focused on situations and state descriptions. Linguistic approaches start with the description of the propositional content of sentences (or natural language expressions generally). As a result, the focus in the two fields has been on different problems. Namely, linguistic theories try to maintain compositionality in the expressions associated with linguistic units, or what is known as semantic compositionality. In AI and in the planning community in particular the focus has been on maintaining compositionality in the way plans are constructed, as well as the correctness of the algorithm that searches and traverses the state space. This can be called plan compositionality. I argue that these approaches have common elements that can be drawn on to view event semantics from a unifying perspective, where we can distinguish between the surface events denoted by verbal predicates and what I refer to as the latent event structure of a sentence. Latent events within a text refer to the finer-grained subeventual representations of events denoted by verbs or nominal expressions, as well as to hidden events connoted by nouns. By clearly distinguishing between surface and latent event structures of sentences and texts, we move closer to a general computational theory of event structure, one permitting a common vocabulary for events and the relations between them, while enabling reasoning at multiple levels of interpretation.

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Literature Review

Zhong¹,

Cambria²

2021

Time Expression and Named Entity Recognition

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KTimeML

Cited by 11 publications

References 3 publications

One, no one and one hundred thousand events: Defining and processing events in an inter-disciplinary perspective

One, no one and one hundred thousand events: Defining and processing events in an inter-disciplinary perspective

The Role of Event-Based Representations and Reasoning in Language

Literature Review

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