Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
119 tokens/sec
GPT-4o
56 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
6 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Three Sentences Are All You Need: Local Path Enhanced Document Relation Extraction (2106.01793v1)

Published 3 Jun 2021 in cs.CL

Abstract: Document-level Relation Extraction (RE) is a more challenging task than sentence RE as it often requires reasoning over multiple sentences. Yet, human annotators usually use a small number of sentences to identify the relationship between a given entity pair. In this paper, we present an embarrassingly simple but effective method to heuristically select evidence sentences for document-level RE, which can be easily combined with BiLSTM to achieve good performance on benchmark datasets, even better than fancy graph neural network based methods. We have released our code at https://github.com/AndrewZhe/Three-Sentences-Are-All-You-Need.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (6)
  1. Quzhe Huang (22 papers)
  2. Shengqi Zhu (6 papers)
  3. Yansong Feng (81 papers)
  4. Yuan Ye (8 papers)
  5. Yuxuan Lai (16 papers)
  6. Dongyan Zhao (144 papers)
Citations (47)

Summary

We haven't generated a summary for this paper yet.