TY - JOUR
T1 - AnswerFinder at QAst 2007
T2 - Named Entity recognition for QA on speech transcripts
AU - Mollá, Diego
AU - Cassidy, Steve
AU - Van Zaanen, Menno
N1 - Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.
PY - 2007
Y1 - 2007
N2 - Macquarie University's contribution to the QAst track of CLEF is centered on a study of Named Entity (NE) recognition on speech transcripts, and how such NE recognition impacts on the accuracy of the final question answering system. We have ported AFNER, the NE recogniser of the AnswerFinder question-answering project, to the types of answer types expected in the QAst track. AFNER uses a combination of regular expressions, lists of names (gazetteers) and machine learning. The machine learning component is a Maximum Entropy classifier and was trained on a development set of the AMI corpus. Problems with scalability of the system and errors of the extracted annotation lead to relatively poor performance in general, though the system was second (out of three participants) in one of the QAst subtasks.
AB - Macquarie University's contribution to the QAst track of CLEF is centered on a study of Named Entity (NE) recognition on speech transcripts, and how such NE recognition impacts on the accuracy of the final question answering system. We have ported AFNER, the NE recogniser of the AnswerFinder question-answering project, to the types of answer types expected in the QAst track. AFNER uses a combination of regular expressions, lists of names (gazetteers) and machine learning. The machine learning component is a Maximum Entropy classifier and was trained on a development set of the AMI corpus. Problems with scalability of the system and errors of the extracted annotation lead to relatively poor performance in general, though the system was second (out of three participants) in one of the QAst subtasks.
UR - http://www.scopus.com/inward/record.url?scp=84921966975&partnerID=8YFLogxK
M3 - Conference paper
AN - SCOPUS:84921966975
SN - 1613-0073
VL - 1173
SP - 1
EP - 9
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
ER -