Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction

Code

• github.com/danilo-dessi/skg
  tf★ 27
• bitbucket.org/luanyi/scierc
  tf★ 0
• github.com/luanyi/DyGIE
  tf★ 0
• github.com/YerevaNN/SciERC
  tf★ 0
• github.com/KeLi-gavin/CS8750
  tf★ 0

Abstract

We introduce a multi-task setup of identifying and classifying entities, relations, and coreference clusters in scientific articles. We create SciERC, a dataset that includes annotations for all three tasks and develop a unified framework called Scientific Information Extractor (SciIE) for with shared span representations. The multi-task setup reduces cascading errors between tasks and leverages cross-sentence relations through coreference links. Experiments show that our multi-task model outperforms previous models in scientific information extraction without using any domain-specific features. We further show that the framework supports construction of a scientific knowledge graph, which we use to analyze information in scientific literature.

Tasks

Benchmark Results

Reproductions