Two-pass named entity classification for cross language question answering
Yu‐Chieh Wu, Kun-chang Tsai, Jie Chi Yang · 2007
In this paper, we present the mono-lingual and bilingual question answering experimental results at NTCIR6-CLQA. We combine most of the online resources and available resources to our QA systems without employing additional resources such as ontology, labeled data. Our method relies on three main important components, namely, passage retrieval, question classifier, and the named entity recognizer. Although our QA model is not state-of-the-art, the attractive of our method is that it was designed fully automatic without further adjusting the