HyTER Networks of Selected OpenMT08/09 Sentences
Item Name: | HyTER Networks of Selected OpenMT08/09 Sentences |
Author(s): | Markus Dreyer, Daniel Marcu |
LDC Catalog No.: | LDC2014T09 |
ISBN: | 1-58563-678-9 |
ISLRN: | 811-846-772-709-6 |
DOI: | https://doi.org/10.35111/ed7d-z579 |
Release Date: | May 15, 2014 |
Member Year(s): | 2014 |
DCMI Type(s): | Text |
Data Source(s): | weblogs, newswire |
Project(s): | NIST MT |
Application(s): | machine translation |
Language(s): | English, Mandarin Chinese, Arabic, Chinese |
Language ID(s): | eng, cmn, ara, zho |
License(s): |
LDC User Agreement for Non-Members |
Licensing Instructions: | Subscription & Standard Members, and Non-Members |
Citation: | Dreyer, Markus, and Daniel Marcu. HyTER Networks of Selected OpenMT08/09 Sentences LDC2014T09. Web Download. Philadelphia: Linguistic Data Consortium, 2014. |
Related Works: | View |
Introduction
HyTER Networks of Selected OpenMT08/09 Progress Set Sentences was developed by SDL and contains HyTER (Hybrid Translation Edit Rate) networks for 102 selected source Arabic and Chinese sentences from OpenMT08 and OpenMT09 Progress Set data. HyTER is an evaluation metric based on large reference networks created by an annotation tool that allows users to develop an exponential number of correct translations for a given sentence. Reference networks can be used as a foundation for developing improved machine translation evaluation metrics and for automating the evaluation of human translation efficiency.
Data
The source material is comprised of Arabic and Chinese newswire and web data collected by LDC in 2007. Annotators created meaning-equivalent annotations under three annotation protocols. In the first protocol, foreign language native speakers built English networks starting from foreign language sentences. In the second, English native speakers built English networks from the best translation of a foreign language sentence as identified by NIST (National Institute of Standards and Technology). In the third protocol, English native speakers built English networks starting from the best translation, but those annotators also had access to three additional, independently produced human translations. Networks created by different annotators for each sentence were combined and evaluated.
This release includes the source sentences and four human reference translations produced by LDC in XML format, along with five machine translation system outputs representing a variety of system architectures and performance, and the human post-edited output of those systems also presented in XML.
Samples
Please view this FST sample and Reference XML sample.
Updates
None at this time.