Log-FGAER: Logic-Guided Fine-Grained Address Entity Recognition from Multi-Turn Spoken Dialogue
Xue Han, Yitong Wang, Qian Hu, Pengwei Hu, Chao Deng, Junlan Feng · 2023
Fine-grained address entity recognition (FGAER) from multi-turn spoken dialogues is particularly challenging.The major reason lies in that a full address is often formed through a conversation process.Different parts of an address are distributed through multiple turns of a dialogue with spoken noises.It is nontrivial to extract by turn and combine them.This challenge has not been well emphasized by main-stream entity extraction algorithms.To address this issue, we propose in this paper a logic-guided fine-grained address recognition method (Log-FGAER), where we formulate the address hierarchy relationship as the logic rule and softly apply it in a probabilistic manner to improve the accuracy of FGAER.In addition, we provide an ontology-based data augmentation methodology that employs ChatGPT to augment a spoken dialogue dataset with labeled address entities.Experiments are conducted using datasets generated by the proposed data augmentation technique and derived from real-world scenarios.The results of the experiment demonstrate the efficacy of our proposal.Where are you in Suzhou city, Jiangsu Prov? 您现在在江苏 苏州市 的哪里？ I'm in Wujiang District, Shengze Town in Wujiang District.