The BioLexicon is a large-scale, wide-coverage computational lexicon covering the biomedical domain. A large part of the lexicon is concerned with covering biomedical terms and their variants. Entries for domain-specific verbs include syntactic and semantic information. The lexicon includes entri...
The corpus consists of 1000 MEDLINE abstracts. It is a subset of the original GENIA POS & term corpus, which was selected using the three MeSH terms human, blood cells and transcription factors. In each sentence, three types of information are annotated 1) biomedical terms are identified and assi...
The Dataset of Nuanced Assertions on Controversial Issues (NAoCI) dataset consists of over 2,000 assertions on sixteen different controversial issues. It has over 100,000 judgments of whether people agree or disagree with the assertions, and of about 70,000 judgments indicating how strongly peopl...
Datasets is arff format (for Weka machine learning software) are made available to reproduce the validation experiments presented in the paper.
This inventory contains a set of terms that are relevant to the study of medical history. The inventory is organised as a set of "heading terms", belonging to one of seven different semantic categories, each of which is accompanied by a set of semantically-related terms. There are around 175,0...
The purpose of the tool is to detect sentence boundaries in English text. The tool is provided as a UIMA component, specifically as Java archive (jar) file, which can be incorporated within any UIMA workflow. However, it is particularly designed use in the U-Compare text mining platform (see sepa...
An academic domain ontology populated using IIT Bombay organization corpus, web and the linked open data.
Adimen-SUMO is an off-the-shelf first-order ontology that has been obtained by reengineering out of the 88% of SUMO (Suggested Upper Merged Ontology). Adimen-SUMO can be used appropriately by FO theorem provers (like E-Prover or Vampire) for formal reasoning.
A corpus of 2,000 MEDLINE abstracts, collected using the three MeSH terms human, blood cells and transcription factors. The corpus is available in three formats: 1) A text file containing part-of-speech (POS) annotation, based on the Penn Treebank format, 2) An XML file containing inline POS anno...
This is a UIMA wrapper for the OpenNLP Tokenizer tool. It assigns part-of-speech tags to tokens in English text. The tagset used in from the Penn Treebank). The tool forms part of the in-built library of components provided with the U-Compare platform (Kano et al., 2009; Kano et al., 2011; see se...