The GENIA tagger analyzes English sentences and outputs the base forms, part-of-speech tags, chunk tags, and named entity tags. The tagger is specifically tuned for biomedical text such as MEDLINE abstracts. The tool is provided as a UIMA component, which forms part of the in-built library of...
Tokenisation is one of the functionalities of the GENIA tagger, which additionally outputs the base forms, part-of-speech tags, chunk tags, and named entity tags. The tagger is specifically tuned for biomedical text such as MEDLINE abstracts. The tool is a UIMA component, which forms part of th...
The purpose of the tool is to identify gene and protein names in biomedical text. The tool is provided as a UIMA component, which forms part of the in-built library of components provided with the U-Compare platform for building and evaluating text mining workflows. The U-Compare Workbench pr...
This is a UIMA wrapper for the OpenNLP Sentence Detector tool. It splits English text into individual sentences. The tool forms part of the in-built library of components provided with the U-Compare platform (see separate META-SHARE record) for building and evaluating text mining workflows. ...
Syntactic parser for English. Outputs dependency relations. Also outputs parts-of-speech for each token. 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-Com...
Part-of-speech tagger tuned to biomedical text. The tool is provided as a UIMA component, which forms part of the in-built library of components provided with the U-Compare platform (see separate META-SHARE record) for building and evaluating text mining workflows. The U-Compare Workbench (se...
Yake! (Campos et al. 2020) is a novel feature-based system for multi-lingual keyword extraction, which supports texts of different sizes, domain or languages. Unlike most of the systems, Yake! does not rely on dictionaries nor thesauri, neither is trained against any corpora. Instead, we follow a...