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  • 1
    Stanford CoreNLP

    Stanford CoreNLP

    Stanford CoreNLP, a Java suite of core NLP tools

    CoreNLP is your one stop shop for natural language processing in Java! CoreNLP enables users to derive linguistic annotations for text, including token and sentence boundaries, parts of speech, named entities, numeric and time values, dependency and constituency parses, coreference, sentiment, quote attributions, and relations. CoreNLP currently supports 6 languages, Arabic, Chinese, English, French, German, and Spanish. The centerpiece of CoreNLP is the pipeline. Pipelines take in raw text,...
    Downloads: 4 This Week
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  • 2
    masmt

    masmt

    A frame work for Multi agent system development

    MaSMT is a java based multi-agent system development framework, especially designed for development of English to Sinhala machine translation system. MaSMT also capable to develop any multi-agent based system through its architecture. Reference: B. Hettige, A. S. Karunananda, G. Rzevski, Multi-agent solution for managing complexity in English to Sinhala Machine Translation, International Journal of Design & Nature and Ecodynamics, Volume 11, Issue 2, 2016, 88 – 96. B. Hettige, A. S....
    Downloads: 1 This Week
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  • 3

    BioC

    We describe a simple XML format to share text documents and annotation

    ...Allows a large number of different annotations to be represented. Project files contain: - simple code to hold/read/write data and perform sample processing. - BioC-formatted corpora - BioC tools that work with BioC corpora BioC goals - simplicity - interoperability - broad use - reuse There should be little investment required to learn to use a format or a software module to process that format. We are interested in reuse, and we focus on common NLP tasks that are broadly useful for textmining.
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    Downloads: 9 This Week
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  • 4
    Phrasal

    Phrasal

    Statistical phrase-based machine translation system

    ...Distinctive features include: providing an easy to use API for implementing new decoding model features, the ability to translating using phrases that include gaps (Galley et al. 2010), and conditional extraction of phrase-tables and lexical reordering models. Developed by The Natural Language Processing Group at Stanford University, a team of faculty, postdocs, programmers and students who work together on algorithms that allow computers to process and understand human languages. Our work ranges from basic research in computational linguistics to key applications in human language technology, and covers areas such as sentence understanding, automatic question answering, machine translation, syntactic parsing and tagging, sentiment analysis.
    Downloads: 0 This Week
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  • 5

    OPTIMA cidoc-crm Semantic Annotation

    Semantic annotation of archaeology reports with respect to CIDOC-CRM

    The semantic annotation system OPTIMA is the result of Andreas Vlachidis PhD work, (supervised by Prof. Douglas Tudhope, University of Glamorgan, UK). OPTIMA performs the NLP tasks of Named Entity Recognition, Relation Extraction, Negation Detection and Word Sense Disambiguation using hand-crafted rules and SKOS terminological resources (English Heritage Thesauri and Glossaries). The resulted semantic annotations are associated with classes of the (ISO 21127:2006) CIDOC Conceptual Reference Model (CRM) and its archaeological extension, CRM-EH. ...
    Downloads: 0 This Week
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  • 6
    The program provides Java interface (to C++ Lemmatizer via XML-RPC) in order to perform lemmatizing in Russian, English, and German (lemma is the canonical form of a lexeme in Natural Language Processing). RussianPOSTagger could work as a module of GATE.
    Downloads: 0 This Week
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