Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/lrec2008/papers/551> ?p ?o. }
Showing items 1 to 13 of
13
with 100 items per page.
- 551 creator stephanie-strassel.
- 551 creator zhiyi-song.
- 551 type InProceedings.
- 551 label "Entity Translation and Alignment in the ACE-07 ET Task".
- 551 sameAs 551.
- 551 abstract "Entities - people, organizations, locations and the like - have long been a central focus of natural language processing technology development, since entities convey essential content in human languages. For multilingual systems, accurate translation of named entities and their descriptors is critical. LDC produced Entity Translation pilot data to support the ACE ET 2007 Evaluation and the current paper delves more deeply into the entity alignment issue across languages, combining the automatic alignment techniques developed for ACE-07 with manual alignment. Altogether 84% of the Chinese-English entity mentions and 74% of the Arabic-English entity mentions are perfect aligned. The results of this investigation offer several important insights. Automatic alignment algorithms predicted that perfect alignment for the ET corpus was likely to be no greater than 55%; perfect alignment on the 15 pilot documents was predicted at 62.5%. Our results suggest the actual perfect alignment rate is substantially higher (82% average, 92% for NAM entities). The careful analysis of alignment errors also suggests strategies for human translation to support the ET task; for instance, translators might be given additional guidance about preferred treatments of name versus nominal translation. These results can also contribute to refined methods of evaluating ET systems.".
- 551 hasAuthorList authorList.
- 551 hasTopic Linguistics.
- 551 isPartOf proceedings.
- 551 keyword "Corpus (creation, annotation, etc.)".
- 551 keyword "Machine Translation, SpeechToSpeech Translation".
- 551 keyword "Named Entity recognition".
- 551 title "Entity Translation and Alignment in the ACE-07 ET Task".