PhenoCHF is an annotated corpus consisting of documents belonging to two different text types (i.e., narrative reports from electronic health records (EHRs) and literature articles). It is manually annotated by medical doctors with detailed information relating to mentions of phenotype concepts a...

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...

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...

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...

Despite many recent papers on Arabic Named Entity Recognition (NER) in the news domain, little work has been done on microblog NER. NER on microblogs presents many complications such as informality of language, shortened named entities, brevity of expressions, and inconsistent capitalization (for...

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...