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This project describes a model of how the semantic human memory represents the information relevant to the objects of the world in text format.
It provides a system and a GUI application capable of extracting and managing concepts and relations from English texts.
https://aseryla2.sourceforge.io/
Semantic Assistants support users in content retrieval, analysis, and development, by offering context-sensitive NLP services directly integrated in standard desktop clients, like a word processor, and web information systems, like a wiki.
The BioNLP UIMA Component Repository provides UIMA wrappers for novel and well-known 3rd-party NLP tools used in biomedical text prosessing, such as tokenizers, parsers, named entity taggers, and tools for evaluation.
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 Wikipedia Miner toolkit provides simplified access to Wikipedia. This open encyclopedia represents a vast, constantly evolving multilingual database of concepts and semantic relations; a promising resource for nlp and related research.
OpenDMAP (Open Source Direct Memory Access Parser) is a natural language processing (text mining) application: a semantic parser for information extraction.
Facilitates data mining/natural language processing experiments to be executed on weblogs, such as classification, clustering and rating. As part of these experiments, it is possible to apply Latent Semantic Analysis.
SYRAH si propone di far emergere e rappresentare i concetti espressi per mezzo di un linguaggio naturale. SYRAH aims to discover and represent concepts expressed in natural languages. NLP, lemma, lemmario, italiano, rete, semantica, clustering, semantic
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AutoSummary uses Natural Language Processing to generate a contextually-relevant synopsis of plain text. It uses statistical and rule-based methods for part-of-speech tagging, word sense disambiguation, sentence deconstruction and semantic analysis.
The OBO-Annotator is a semantic NLP tool that is designed to give its end-users a great deal of flexibility to combine any number of OBO ontologies from the OBO foundry regardless of their format and use them to annotate text-bases.