title: Wide-coverage relation extraction from MEDLINE using deep syntax.
abstract: BACKGROUND
  Relation extraction is a fundamental technology in biomedical text mining. Most of the previous studies on relation extraction from biomedical literature have focused on specific or predefined types of relations, which inherently limits the types of the extracted relations. With the aim of fully leveraging the knowledge described in the literature, we address much broader types of semantic relations using a single extraction framework.
  
  
  RESULTS
  Our system, which we name PASMED, extracts diverse types of binary relations from biomedical literature using deep syntactic patterns. Our experimental results demonstrate that it achieves a level of recall considerably higher than the state of the art, while maintaining reasonable precision. We have then applied PASMED to the whole MEDLINE corpus and extracted more than 137 million semantic relations. The extracted relations provide a quantitative understanding of what kinds of semantic relations are actually described in MEDLINE and can be ultimately extracted by (possibly type-specific) relation extraction systems.
  
  
  CONCLUSIONS
  PASMED extracts a large number of relations that have previously been missed by existing text mining systems. The entire collection of the relations extracted from MEDLINE is publicly available in machine-readable form, so that it can serve as a potential knowledge base for high-level text-mining applications.
authors.affiliation: School of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa, Japan. nthnhung@jaist.ac.jp.
authors.forename: Nhung T H
authors.initials: NT
authors.lastname: Nguyen
authors.affiliation: Toyota Technological Institute, Nagoya, Japan. makoto-miwa@toyota-ti.ac.jp.
authors.forename: Makoto
authors.initials: M
authors.lastname: Miwa
authors.affiliation: Graduate School of Engineering, The University of Tokyo, Tokyo, Japan. tsuruoka@logos.t.u-tokyo.ac.jp.
authors.forename: Yoshimasa
authors.initials: Y
authors.lastname: Tsuruoka
authors.affiliation: Graduate School of Engineering, The University of Tokyo, Tokyo, Japan. chikayama@logos.t.u-tokyo.ac.jp.
authors.forename: Takashi
authors.initials: T
authors.lastname: Chikayama
authors.affiliation: School of Information Science, Japan Advanced Institute of Science and Technology, Ishikawa, Japan. tojo@jaist.ac.jp.
authors.forename: Satoshi
authors.initials: S
authors.lastname: Tojo
mesh_terms: D057225:Data Mining / Q000379:methods*; D016239:MEDLINE; D012660:Semantics