Corpus ID: 7558249

Collective Cross-Document Relation Extraction Without Labelled Data

@inproceedings{Yao2010CollectiveCR,
  title={Collective Cross-Document Relation Extraction Without Labelled Data},
  author={Limin Yao and S. Riedel and A. McCallum},
  booktitle={EMNLP},
  year={2010}
}

Limin Yao, S. Riedel, A. McCallum

Published in EMNLP 2010

Computer Science

We present a novel approach to relation extraction that integrates information across documents, performs global inference and requires no labelled text. In particular, we tackle relation extraction and entity identification jointly. We use distant supervision to train a factor graph model for relation extraction based on an existing knowledge base (Freebase, derived in parts from Wikipedia). For inference we run an efficient Gibbs sampler that leads to linear time joint inference. We evaluate… CONTINUE READING

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