Translating Named Entities Using Monolingual and Bilingual Resources
نویسندگان
چکیده
Named entity phrases are some of the most difficult phrases to translate because new phrases can appear from nowhere, and because many are domain specific, not to be found in bilingual dictionaries. We present a novel algorithm for translating named entity phrases using easily obtainable monolingual and bilingual resources. We report on the application and evaluation of this algorithm in translating Arabic named entities to English. We also compare our results with the results obtained from human translations and a commercial system for the same task.
منابع مشابه
EFL Translation Students' Perspective toward Using Bilingual Dictionary in Translation of Polysemous Words
This research presented the use of bilingual dictionary and addressed the EFL translation students' points of view on the use of bilingual dictionary in translating polysemous words (English to Persian). Moreo- ver, it aimed at finding the possible relationship between the effect of using bilingual dictionary by stu- dents in translating polysemous words and their achieved scores. In the study ...
متن کاملNamed Entities Translation Based On Comparable Corpora
In this paper we present a system for translating named entities from Basque to Spanish based on comparable corpora. For that purpose we have tried two approaches: one based on Basque linguistic features, and a language-independent tool. For both tools we have used BasqueSpanish comparable corpora, a bilingual dictionary and the web as resources.
متن کاملWord-Transliteration Alignment
The named-entity phrases in free text represent a formidable challenge to text analysis. Translating a named-entity is important for the task of Cross Language Information Retrieval and Question Answering. However, both tasks are not easy to handle because named-entities found in free text are often not listed in a monolingual or bilingual dictionary. Although it is possible to identify and tra...
متن کاملEffective Bilingual Constraints for Semi-Supervised Learning of Named Entity Recognizers
Most semi-supervised methods in Natural Language Processing capitalize on unannotated resources in a single language; however, information can be gained from using parallel resources in more than one language, since translations of the same utterance in different languages can help to disambiguate each other. We demonstrate a method that makes effective use of vast amounts of bilingual text (a....
متن کاملUsing Word Embeddings to Translate Named Entities
In this paper we investigate the usefulness of neural word embeddings in the process of translating Named Entities (NEs) from a resource-rich language to a language low on resources relevant to the task at hand, introducing a novel, yet simple way of obtaining bilingual word vectors. Inspired by observations in (Mikolov et al., 2013b), which show that training their word vector model on compara...
متن کامل