@Article{Hermjakob2018,
author="Hermjakob, Ulf
and Li, Qiang
and Marcu, Daniel
and May, Jonathan
and Mielke, Sebastian J.
and Pourdamghani, Nima
and Pust, Michael
and Shi, Xing
and Knight, Kevin
and Levinboim, Tomer
and Murray, Kenton
and Chiang, David
and Zhang, Boliang
and Pan, Xiaoman
and Lu, Di
and Lin, Ying
and Ji, Heng",
title="Incident-Driven Machine Translation and Name Tagging for Low-resource Languages",
journal="Machine Translation",
year="2018",
month="Jun",
day="01",
volume="32",
number="1",
pages="59--89",
abstract="We describe novel approaches to tackling the problem of natural language processing for low-resource languages. The approaches are embodied in systems for name tagging and machine translation (MT) that we constructed to participate in the NIST LoReHLT evaluation in 2016. Our methods include universal tools, rapid resource and knowledge acquisition, rapid language projection, and joint methods for MT and name tagging.",
issn="1573-0573",
doi="10.1007/s10590-017-9207-1",
url="https://doi.org/10.1007/s10590-017-9207-1"
}