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...
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. ...
Web service created by exporting UIMA-based workflow from the U-Compare text mining system. Functionality: Identifies clauses/segments in plain text. Also identifies sentences, tokens, POS tags and lemmas. Tools in workflow: Cafetiere Sentence Splitter (University of Manchester), TTL Tokenizer...
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...
Web service created by exporting UIMA-based workflow from the U-Compare text mining system. Functionality: Identifies co-reference chains in plain text. Also identifies sentences, tokens with parts-of-speech and lemmas, and NP chunks Tools in workflow: TTL-Tokenizer (RACAI, Romania), TTL-Tagger...
Web service created by exporting UIMA-based workflow from the U-Compare text mining system. Functionality: Identifies NP chunks in plain text. Also carries out sentence splitting, tokenisation and POS tagging Tools in workflow: MLRS Sentence Splitter (University of Malta), UAIC-POSTagger, UAIC-...
Automatically generated corpus of 98,818 graph/string pairs.
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...
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...