LX-Tagger is a freely available online service for the part-of-speech tagging of Portuguese. It was developed and is mantained by the NLX-Natural Language and Speech Group at the University of Lisbon, Department of Informatics. The service is composed by a set of shallow processing tools: A se...
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LX-UDParser is a UD parser for Portuguese, which adopts the Universal Dependency framework, with an initial performance of 90.87 for UAS and 88.01 for LAS under a ten-fold cross validation scheme. It is described in this article: António Branco, João Ricardo Silva, Luís Gomes and João Rodri...
Web service created by exporting UIMA-based workflow from the U-Compare text mining system. Functionality: Identifies sentences and tokens in plain text. Parts of speech and lemmas are assigned to tokens. Language is automatically identified amongst the supported languages and language-specific ...
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.
LX-Lemmatizer is a freely available online service for fully-fledged lemmatization of Portuguese verbs. It was developed and is maintained at University of Lisbon by the NLX-Natural Language and Speech Group of the Department of Informatics. LX-Lemmatizer takes a Portuguese verb form and deliv...
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The purpose of the U-Compare platform is to facilitate easy and rapid development and evaluation of NLP and text mining systems. It includes utilities (including a graphical user interface, the U-Compare workbench, see separate record in META-SHARE) to create workflows from individual, interopera...
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.