A language identifier for closely related languages.

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...

Uplug (see Tiedemann, 2003a) is a collection of tools and scripts for processing text-corpora, for automatic alignment and for term extraction from parallel corpora. Several tools have been integrated in Uplug. Pre-processing tools include a sentence splitter, a general tokenizer and wrappers a...

Lince is a multi-platform stand-alone application that updates the textual contents of documents in a range of popular formats to the spelling prescribed by the 1990 Portuguese language reform. It works with both previously existing Portuguese language orthographic standards (1943, previously val...

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...

Web service created by exporting UIMA-based workflow from the U-Compare text mining system. Functionality: Performs discourse parsing on plain text. Also identifies sentences, tokens, parts of speech, lemmas, clauses and coreference chains Tools in workflow: UAIC-POSTagger, UAIC-NPChunker, UAI...

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...

Enju is a syntactic parser for English. The grammar used by the parser is based on Head Driven Phrase Structure Grammar (HPSG). Enju can analyse syntactic/semantic structures of English sentences can output phrase structure and predicate-argument structures.

TinySVM is an implementation of Support Vector Machines (SVMs) (Vapnik, 1995; Vapnik, 1998) for the problem of pattern recognition.

MSTParser is a non-projective dependency parser (see McDonald et al., 2005a, 2006) that searches for maximum spanning trees over directed graphs. Models of dependency structure are based on large-margin discriminative training methods (see McDonald et al., 2005b). Projective parsing is also suppo...