Chinese Question-Answering: Comparing Monolingual with English-Chinese Cross-Lingual Results

摘要

A minimal approach to Chinese factoid QA is described. It employs entity extraction software, template matching, and statistical candidate answer ranking via five evidence types, and does not use explicit word segmentation or Chinese syntactic analysis. This simple approach is more portable to other Asian languages, and may serve as a base on which more precise techniques can be used to improve results. Applying to the NTCIR-5 monolingual environment, it delivers medium top-1 accuracy and MRR of .295, .3381 (supported answers) and .41, .4998 (including unsupported) respectively. When applied to English-Chinese cross language QA with three different forms of English-Chinese question translation, it attains top-1 accuracy and MRR of .155, .2094 (supported) and .215, .2932 (unsupported), about ～52% to ～62% of monolingual effectiveness. CLQA improvements via successively different forms of question translation are also demonstrated.