FA Team at the NTCIR-17 UFO Task
Yuki Okumura Masato Fujitake
The FA team participated in the Table Data Extraction (TDE) and Text-to-Table
Relationship Extraction (TTRE) tasks of the NTCIR-17 Understanding of
Non-Financial Objects in Financial Reports (UFO). This paper reports our
approach to solving the problems and discusses the official results. We
successfully utilized various enhancement techniques based on the ELECTRA
language model to extract valuable data from tables. Our efforts resulted in an
impressive TDE accuracy rate of 93.43 %, positioning us in second place on the
Leaderboard rankings. This outstanding achievement is a testament to our
proposed approach's effectiveness. In the TTRE task, we proposed the rule-based
method to extract meaningful relationships between the text and tables task and
confirmed the performance.