Low Resource Languages for Emergent Incidents (LORELEI) is a DARPA-sponsored program. The goal of the program is to dramatically advance the state of computational linguistics and human language technology to enable rapid, low-cost development of capabilities for low-resource languages.
This web page serves as a portal for all information pertaining to the Low Resource (LoRe) HLT open evaluations of component technologies relevant to LORELEI. For general questions and comments, please e-mail lorehlt_poc [at] nist.gov (lorehlt_poc[at]nist[dot]gov). For more information about a specific evaluation cycle, including evaluation documentation, see the year-specific sections below. For general announcements and discussing regarding the LoReHLT evaluation series, you can subscribe to the LoReHLT mailing list hosted by NIST, lorehlt [at] nist.gov (lorehlt[at]nist[dot]gov), by sending e-mail to lorehlt_list-requeset [at] nist.gov (lorehlt_list-request[at]nist[dot]gov) with "subscribe" in the subject line.
Tasks
- Machine translation (MT)
- Entity Discovery and Linking (EDL)
- Situation Frame (SF)
- Sentiment, Emotion, & Cognitive State (SEC) (Pilot)
Highlights
- Surprise language evaluation (two surprise languages)
- New SEC pilot evaluation
- Two evaluation checkpoints to gauge performance based on time and training resources given
Documentation
Tools
Tasks
- Machine translation (MT)
- Entity Discovery and Linking (EDL)
- Situation Frame (SF)
Highlights
- Surprise language evaluation (two surprise languages)
- Two training conditions: constrained (required) and unconstrained
- Two evaluation checkpoints to gauge performance based on time and training resources given
Registration
Documentation
Tools
Publications and System Descriptions
Tasks
- Machine translation (MT)
- Entity Discovery and Linking (EDL)
- Situation Frame (SF)
Highlights
- Surprise language evaluation (two surprise languages)
- Two training conditions: constrained (required) and unconstrained
- Three evaluation checkpoints to gauge performance based on time and training resources given
Documentation
Tools
- Test data encryption package: OpenSSLTest-v2.tar.bz2 (md5)
- MT:
- EDL:
- Situation Frame (Text):
- Situation Frame (Speech) -- We would like to thank the Signal Analysis and Interpretation Laboratory (SAIL) at the University of Southern California for provided the scoring software for the Situation Frame Speech task:
Publications and System Descriptions
Tasks
- Machine translation (MT)
- Situation Frame (SF)
- Named entity recognition (NER)
Highlights
- Surprise language evaluation
- Two training conditions: constrained (required) and unconstrained
- Three evaluation checkpoints to gauge performance based on time and training resources given
Documentation
Tools
Publications and System Descriptions
Disclaimer
Any mention of commercial products within NIST web pages is for information only; it does not imply recommendation or endorsement by NIST.