FYI


-------- Missatge reenviat --------
Assumpte: [Mt-list] LoReHLT 2017 Low-Resource Language Technology evaluation
Data:   Wed, 15 Feb 2017 16:28:39 +0000
De:     Soboroff, Ian (Fed) <[email protected]>
A:      [email protected] <[email protected]>



Dear All,

NIST is pleased to announce the second Low Resource Human Language Technology 
Evaluation (LoReHLT17) to support the development of human language technology 
(HLT) that can provide rapid and effective response to emerging incidents where 
the language resources are very limited. The evaluation consists of three tasks:

 - Machine Translation
 - Entity Discovery and Linking
 - Situation Frame (lightweight event extraction)

As with the first LoReHLT evaluation, participants may choose to participate in 
any or all of the above tasks.

In LoReHLT, the evaluation language is a surprise, and is announced at the start of the 
evaluation period.  The evaluation centers on an emergency scenario, such as a tsunami or 
earthquake, where humanitarian assistance and disaster relief agencies need situational 
awareness support but have no NLP technology available to deploy.  There is no training 
data in the evaluation language per se.  Instead, participants are invited to pivot from 
other related languages, take advantage of language "universals", use 
transliteration, or attempt to quickly bootstrap training resources during the evaluation.

For year two, there will actually be TWO surprise evaluation languages released 
simultaneously.  You can do one or both.  There will be a dry-run in July and 
the format evaluation period is in August, 2017.

The LDC has made a number of resources available in "related languages", 
including Hungarian, Amharic, Uzbek, Vietnamese, Farsi and more. Participants are invited 
to use these resources as starting points to pivot to the surprise evaluation language.

For further information regarding the evaluation and schedule, please consult 
the evaluation plan which can be found at 
https://www.nist.gov/itl/iad/mig/lorehlt17-evaluations

We look forward to your participation LoReHLT17.
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