An Arabic twitter data set of 7,503 tweets. The released data contains manual Sentiment Analysis annotations as well as automatically extracted features, saved in Comma Separated (CSV) and Attribute-Relation File Format (ARFF) file formats. Due to twitter privacy restrictions we replaced the orig...
This is a workflow that is designed especially for use in the UIMA-based U-Compare workbench (see separate META-SHARE record). The workflow is in "ucz" format (specific to U-Compare) and can be imported via the "Import Workflow" item in the "Workflows" menu of the U-Compare interface. It include...
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...
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...
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. ...
The resource constitues of a hierarchically-structured system of data types, which is intended to be suitable for describing the inputs and output annotation types of a wide range of natural language processing applications which operate within the UIMA Framework. It is being developed in conjunc...
Web service created by exporting UIMA-based workflow from the U-Compare text mining system. Functionality: Carries out syntactic parsing on plain text Tools in workflow: Cafetiere Sentence Splitter (University of Manchester), OpenNLP Tokenizer (Apache), STEPP Tagger (University of Manchester), ...
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 detect sentence boundaries in English text. It is trained on the GENIA corpus of biomedical abstracts and so is particularly suitable for splitting sentences in biomedical texts. The tool is provided as a UIMA component, which forms part of the in-built library of co...
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...