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MER: a shell script and annotation server for minimal named entity recognition and linking.

Francisco M Couto1, Andre Lamurias2,3

  • 1LASIGE, Faculdade de Ciências, Universidade de Lisboa, 1749 016, Lisbon, Portugal. fcouto@di.fc.ul.pt.

Journal of Cheminformatics
|December 7, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces MER, a fast and flexible named-entity recognition and linking tool. MER efficiently annotates text using simple inputs or ontologies, achieving rapid processing times.

Keywords:
Annotation serverBiomedical ontologiesEntity linkingLexiconNamed-entity recognitionText mining

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Area of Science:

  • Bioinformatics
  • Natural Language Processing
  • Computational Biology

Background:

  • Named-entity recognition (NER) is crucial for identifying specific terms in text for knowledge base linking.
  • Existing tools often require complex setups or extensive resources.
  • There is a need for efficient and flexible NER tools in scientific text analysis.

Purpose of the Study:

  • To present MER, a minimal, flexible, autonomous, and efficient named-entity recognition and linking tool.
  • To demonstrate MER's capability in processing scientific texts rapidly.
  • To offer MER as a publicly available resource for the research community.

Main Methods:

  • MER utilizes a lexicon and optional link files, or generates them from an ontology.
  • It leverages high-performance Unix command-line tools (grep, awk) and an inverted recognition technique.
  • The tool was deployed on cloud infrastructure for large-scale annotation tasks.

Main Results:

  • MER processed documents in under 3 seconds per document on average, without caching.
  • It achieved competitive precision and recall compared to state-of-the-art dictionary lookup methods.
  • The tool demonstrated high computational performance and reliability in the BioCreative V.5 challenge.

Conclusions:

  • MER provides an efficient, flexible, and autonomous solution for named-entity recognition and linking.
  • Its performance and ease of use make it a valuable tool for scientific text annotation.
  • MER is accessible via GitHub and a RESTful Web service, promoting wider adoption.