NUL System at NTCIR RITE-VAL Tasks

This paper describes the submitted strategy and the methods of NUL team on NTCIR-11 RITE-VAL[1] fact validation (FV) and system validation (SV) tasks. We started to follow the shallow approach by Tian et al[3]. Then, we improved the named entity recognition accuracy and transformed some variables by the cross validation score of training sets. Especially, in the FV tasks, we used Apache Solr as the base search system. We compared several units of chunk to the texts index and the weighting of the ranking score for search results. After several modification, we achieved the highest cross validation score to the RITE-10 Exam bc and Exam Search tasks. Our final submitted system achieved Macro-f1 score 61.93 in FV and 69.59 in SV respectively.