Construction of the Literature Graph in Semantic Scholar
Computation and Language
2018-05-08 v1
Abstract
We describe a deployed scalable system for organizing published scientific literature into a heterogeneous graph to facilitate algorithmic manipulation and discovery. The resulting literature graph consists of more than 280M nodes, representing papers, authors, entities and various interactions between them (e.g., authorships, citations, entity mentions). We reduce literature graph construction into familiar NLP tasks (e.g., entity extraction and linking), point out research challenges due to differences from standard formulations of these tasks, and report empirical results for each task. The methods described in this paper are used to enable semantic features in www.semanticscholar.org
Keywords
Cite
@article{arxiv.1805.02262,
title = {Construction of the Literature Graph in Semantic Scholar},
author = {Waleed Ammar and Dirk Groeneveld and Chandra Bhagavatula and Iz Beltagy and Miles Crawford and Doug Downey and Jason Dunkelberger and Ahmed Elgohary and Sergey Feldman and Vu Ha and Rodney Kinney and Sebastian Kohlmeier and Kyle Lo and Tyler Murray and Hsu-Han Ooi and Matthew Peters and Joanna Power and Sam Skjonsberg and Lucy Lu Wang and Chris Wilhelm and Zheng Yuan and Madeleine van Zuylen and Oren Etzioni},
journal= {arXiv preprint arXiv:1805.02262},
year = {2018}
}
Comments
To appear in NAACL 2018 industry track