38,337 research outputs found
SemEval 2017 Task 10: ScienceIE - Extracting Keyphrases and Relations from Scientific Publications
We describe the SemEval task of extracting keyphrases and relations between
them from scientific documents, which is crucial for understanding which
publications describe which processes, tasks and materials. Although this was a
new task, we had a total of 26 submissions across 3 evaluation scenarios. We
expect the task and the findings reported in this paper to be relevant for
researchers working on understanding scientific content, as well as the broader
knowledge base population and information extraction communities
Global Normalization of Convolutional Neural Networks for Joint Entity and Relation Classification
We introduce globally normalized convolutional neural networks for joint
entity classification and relation extraction. In particular, we propose a way
to utilize a linear-chain conditional random field output layer for predicting
entity types and relations between entities at the same time. Our experiments
show that global normalization outperforms a locally normalized softmax layer
on a benchmark dataset.Comment: EMNLP 201
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