My name is Marcus Nitzschke and I’m studying computer science at the University of Leipzig. This implementation was written as the practical course of the lecture “Software aus Komponenten” in autumn 2011. Generally I chose this topic because I’m interested in the techniques of the Semantic Web and in detail because the connection of these techniques and NLP applications meant a new experience to me.

Due to the website, “MontyLingua is a free, commonsense-enriched, end-to-end natural language understander for English”. The commonsense-enriched part let MontyLingua differ from various other NLP tools. MontyLingua combines a Tokenizer, Part-of-speech Tagger, Extractor, Lemmatiser and a so called NLGenerator, which generates naturalistic English sentences and text summaries.

Because MontyLingua is written in Python this is one of the first non-Java wrapper for NLP2RDF (Monty also provides a Java binary, but Python is more fun :) ). The wrapper currently implements the Part-of-speech Tagger component of MontyLingua. For future work it would be interesting to extract informations of word relationships which are provided by MontyLingua.

Homepage Montylingua
Additionalparameter None
Status NIF 1.0 compliant without RDF/XML input and given error handling.

RDF | JSON | N3 | NTriples

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