Tong, A.
, Diduch, L.
, Fiscus, J.
, Haghpanah, Y.
, Huang, S.
, Joy, D.
, Peterson, K.
and Soboroff, I.
(2017),
Overview of the NIST 2016 LoReHLT Evaluation, Machine Translation Special Issue NLP in Low Resource Languages, [online], https://doi.org/10.1007/s10590-017-9200-8
(Accessed November 20, 2024)
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Overview of the NIST 2016 LoReHLT Evaluation
Published
Author(s)
, , , , , , ,
Abstract
Initiated in conjunction with DARPA's Low Resource Languages for Emergent Incidents (LORELEI) Program, the NIST LoReHLT (Low Re-source Human Language Technology) evaluation series seeks to incubate research on fundamental natural language processing tasks in under-resourced languages. While part of the LORELEI program, LoReHLT is an open evaluation workshop that anyone may participate and had its fi rst evaluation in July 2016. A total of eight teams out of 21 registrants participated in the evaluation over three tasks - machine translation, named entity recognition, and situation frame - in the surprise language Uyghur.Citation
Machine Translation Special Issue NLP in Low Resource Languages
Pub Type
Journals
Download Paper
Keywords
low resource human language technology evaluation, machine translation evaluation, named entity recognition evaluation, situation frame evaluation, Uyghur
Citation
Issues
If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.
Created November 13, 2017, Updated November 10, 2018