Web service created by exporting UIMA-based workflow from the U-Compare text mining system. Functionality: Identifies biological named entities and disambiguates them according to species, by assigning a species ID from the NCBI taxonomy. Also identifies sentences and tokens. Tools in workflow...

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.

Web service created by exporting UIMA-based workflow from the U-Compare text mining system. Functionality: Identifies biomedical named entities (genes and proteins) in plain text. Also identifies sentences. Tools in workflow: Cafetiere Sentence Splitter (University of Manchester), NEMine (Univ...

Treat is a toolkit for natural language processing and computational linguistics in Ruby. The Treat project aims to build a language- and algorithm- agnostic NLP framework for Ruby with support for tasks such as document retrieval, text chunking, segmentation and tokenization, natural language pa...

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...

LX-NER is a freely available online service for the recognition of expressions for named entities in Portuguese. It was developed and is maintained by the NLX-Natural Language and Speech Group at the University of Lisbon, Department of Informatics. LX-NER takes a segment of Portuguese text an...