Mention Detection Crossing the Language Barrier

While significant effort has been put into annotating linguistic resources for several languages, there are still many left that have only small amounts of such resources. This paper investigates a method of propagating information (specifically mention detection information) into such low resource languages from richer ones. Experiments run on three language pairs (Arabic-English, Chinese-English, and Spanish-English) show that one can achieve relatively decent performance by propagating information from a language with richer resources such as English into a foreign language alone (no resources or models in the foreign language). Furthermore, while examining the performance using various degrees of linguistic information in a statistical framework, results show that propagated features from English help improve the source-language system performance even when used in conjunction with all feature types built from the source language. The experiments also show that using propagated ...

• Type: Conference
• Year: 2008
• Where: EMNLP
• Authors: Imed Zitouni, Radu Florian
• Keywords: EMNLP 2007, EMNLP 2008, Feature Types, Foreign Language, Linguistic Resources, Natural Language Processing