Published June 27, 2021 | Version 1.0
Dataset Open

Complete Medline abstracts corpus between 2015-2019 annotated Whatizit text annotation tool

  • 1. scientific assistant - working student
  • 2. Graduate associate
  • 3. Team Lead
  • 4. Head

Description

Background:

Whatizit is a text processing system that allows you to do text-mining tasks on text. It is great at identifying molecular biology terms and linking them to publicly available databases. Identified terms are wrapped with XML tags that carry additional information, such as the primary keys to the databases where all the relevant information is kept. The wrapping XML is translated into HTML hypertext links. This service is highly appreciated by people who are reading literature and need to quickly find more information about a particular term, e.g. its Gene Ontology term.

Whatizit is used in identifying formalized language patterns, specialized, syntactically formalized, technical notation. The annotation speed of a given pipeline is almost independent of the size of the vocabulary behind it and is currently based on pattern matching. In addition, several vocabularies can be integrated in a single pipeline.

Methodology:

The pipeline used is comprised of 175k Gene Ontology terms (preferred labels + synonyms).
The annotation on Medline 2015-2019 corpus is done with  Gene Ontology (GO) integrated dictionary.

The .zip file contains 10 XML files - each file is for half an year of MEDLINE annotated abstracts.
In addition to the abstract, the title is also annotated for further information enrichment.

Respective DOIs, PMIDs are also included in the XML, when applicable.

Further development:

The XML files can be converted into JSON, JSON-LD format.

 

 

Files

medline_tagged.zip

Files (2.5 GB)

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md5:f7be406a096398fa3d40f7ee3f6f34c3
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