DeepAI AI Chat
Log In Sign Up

InSRL: A Multi-view Learning Framework Fusing Multiple Information Sources for Distantly-supervised Relation Extraction

by   Zhendong Chu, et al.

Distant supervision makes it possible to automatically label bags of sentences for relation extraction by leveraging knowledge bases, but suffers from the sparse and noisy bag issues. Additional information sources are urgently needed to supplement the training data and overcome these issues. In this paper, we introduce two widely-existing sources in knowledge bases, namely entity descriptions, and multi-grained entity types to enrich the distantly supervised data. We see information sources as multiple views and fusing them to construct an intact space with sufficient information. An end-to-end multi-view learning framework is proposed for relation extraction via Intact Space Representation Learning (InSRL), and the representations of single views are jointly learned simultaneously. Moreover, inner-view and cross-view attention mechanisms are used to highlight important information on different levels on an entity-pair basis. The experimental results on a popular benchmark dataset demonstrate the necessity of additional information sources and the effectiveness of our framework. We will release the implementation of our model and dataset with multiple information sources after the anonymized review phase.


Multi-view Inference for Relation Extraction with Uncertain Knowledge

Knowledge graphs (KGs) are widely used to facilitate relation extraction...

Leveraging 2-hop Distant Supervision from Table Entity Pairs for Relation Extraction

Distant supervision (DS) has been widely used to automatically construct...

HiCLRE: A Hierarchical Contrastive Learning Framework for Distantly Supervised Relation Extraction

Distant supervision assumes that any sentence containing the same entity...

CANDiS: Coupled & Attention-Driven Neural Distant Supervision

Distant Supervision for Relation Extraction uses heuristically aligned t...

Dynamic Multi-View Fusion Mechanism For Chinese Relation Extraction

Recently, many studies incorporate external knowledge into character-lev...

Joint Structured Models for Extraction from Overlapping Sources

We consider the problem of jointly training structured models for extrac...

Logician: A Unified End-to-End Neural Approach for Open-Domain Information Extraction

In this paper, we consider the problem of open information extraction (O...