Argument Structure in TimeML

Authors James Pustejovsky, Jessica Littman, Roser Sauri



PDF
Thumbnail PDF

File

DagSemProc.05151.4.pdf
  • Filesize: 423 kB
  • 14 pages

Document Identifiers

Author Details

James Pustejovsky
Jessica Littman
Roser Sauri

Cite As Get BibTex

James Pustejovsky, Jessica Littman, and Roser Sauri. Argument Structure in TimeML. In Annotating, Extracting and Reasoning about Time and Events. Dagstuhl Seminar Proceedings, Volume 5151, pp. 1-14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2006) https://doi.org/10.4230/DagSemProc.05151.4

Abstract

TimeML is a specification language for the annotation of events and temporal expressions in natural language text. In addition, the language introduces three relational tags linking temporal objects and events to one another. These links impose both aspectual and temporal ordering over time objects, as well as mark up subordination contexts introduced by modality,  evidentiality, and factivity. Given the richness of this specification, the TimeML working group decided not to include the arguments of  events within the language specification itself. Full reasoning and inference over natural language texts clearly requires knowledge of events along with their participants. In this paper, we define the appropriate role of argumenthood within event markup and propose that  TimeML should make a basic distinction between arguments that are events and those that are  entities. 
We first review how TimeML treats event arguments in subordinating and aspectual contexts, creating event-event relations between predicate and argument.  
As it turns out, these constructions cover a large number of the argument types selected for by event predicates.  We suggest that TimeML be enriched slightly to include causal predicates, such as {it lead to}, since these also involve event-event relations. We propose that all other verbal arguments  be ignored by the specification, and any predicate-argument binding of participants to an event should be performed by independent means. In fact, except for the event-denoting arguments handled by the extension to TimeML proposed here, almost full temporal ordering of the events in a text can be computed without argument identification.

Subject Classification

Keywords
  • Temporal annotation
  • event expressions
  • argument structure

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail