[Corpora-List] event-participants-time-location-etc tagger

Joel Nothman joel at it.usyd.edu.au
Tue Dec 17 21:22:19 UTC 2013


Hi Fatemeh,

On Wed, Dec 18, 2013 at 4:47 AM, Fatemeh Torabi Asr <torabiasr at gmail.com>wrote:

> Hi all,
>
> Does anybody know of the latest [state-of-the-art] [efficient] [open
> source] package or toolkit for detecting events plus whatever within
> document information about them (the more the better).
>
> Most favorable example which I copy from FASTUS old paper:
>
> *Incident: Date*                   - 19 Apr 89*Incident: Location*               El Salvador: San Salvador (CITY)*Incident: Type*                   Bombing*Perpetrator: Individual ID*      "urban guerrillas"*Perpetrator: Organization ID*     "FMLN"*Perpetrator: Organization*        Suspected or Accused by Authorities:  "FMLN"
>                *Confidence*        *Physical Target: Description*     "vehicle"*Physical Target: Effect*          Some Damage:  "vehicle"*Human Target: Name*               "Roberto Garcia Alvarado"*Human Target: Description*        "attorney general": "Roberto Garcia Alvarado"
> 				 "driver"
> 				 "bodyguards"*Human Target: Effect*             Death: "Roberto Garcia Alvarado"
>  			         No Injury: "driver"
> 				 Injury: "bodyguards"
>
> This sort of extraction is very task-dependent (do you actually want to
extract Latin American terrorist incidents?), and I'm not sure what's
available as software.

> A second related question: is TARSQI the best implementation of the TimeML which is readily available?
>
> No. Some of the systems that performed well at the recent TempEval
evaluations of TimeML technology are available online:

   - TIMEE/TIPSem by Hector Llorens:
http://gplsi.dlsi.ua.es/demos/TIMEE/ (binary
   release)
   - ClearTk,including Steven Bethard's TimeML tagger:
   https://code.google.com/p/cleartk/ (open-source, built on UIMA)

Other tools are available for individual components of the task, such as
temporal expression recognition and normalisation (e.g.
https://code.google.com/p/heideltime/).

Cheers,

Joel Nothman
Schwa Lab
School of IT
University of Sydney
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