Search Results for "tagging"

AlohaMini is a lightweight self-hostable productivity and note-taking platform designed to help individuals organize thoughts, tasks, and knowledge in a fast, minimal interface that avoids unnecessary complexity. It combines hierarchical notebooks, rich text editing, and tagging, allowing users to structure information the way they think and refine that structure over time. The platform focuses on speed and responsiveness, with a UI that loads instantly and feels smooth even on modest hardware, making it ideal for both desktop and small server deployments. AlohaMini also supports internal linking between notes, enabling a web-like connected knowledge space that grows organically as users create and connect ideas. ...

Aelius is an ongoing open source project aiming at developing a suite of Python, NLTK-based modules and interfaces to external freely available tools for shallow parsing of Brazilian Portuguese. It also includes language resources such as language models, sample texts, and gold standards. Presently, Aelius already offers facilities for POS-tagging and chunking corpora and outputting annotations in different formats, such as in XML in the TEI P5 encoding scheme.

SCAN (Smart Content Aggregation and Navigation) is a universal semantic content aggregator. It combines search, text analysis, tagging and metadata functions to provide new user experience of desktop navigation and document management.

...Plinko should identify and parse the data completely without the sending system caring what it sent. The latest version supports named fields in the STL files for tagging data parsed in the Prefix Tree and anonymous functions for parsing dynamic message payloads. We now output JSON objects and I'm working on HBase integration. By outputting to JSON it also leaves open the possibility for on the fly in memory correlation between events. Read the included README before starting, it has a quick start guide and info on the constructors.

HanNanum is a Korean Morphological Analyzer and POS Tagger. A plug-in component-based architecture is adapted to the new Java version for flexible use. You can find the work flow for morphological analysis, POS tagging, noun extraction, etc. Contact: kschoi@kaist.ac.kr hjjeong@world.kaist.ac.kr

TagSEA is a framework for tagging locations of interest within Eclipse. Visit our project page for more information - including downloads and documentation: tagsea.sourceforge.net

The Rudify tools are a collection of tools for ontology tagging.

Maximum entropy is a powerful method for constructing statistical models of classification tasks, such as part of speech tagging in Natural Language Processing. Several example applications using maxent can be found in the OpenNLP Tools Library.

Based on the Buckwalter Morphological Analyzer (Version 1.0) for doing Arabic stemming and POS tagging. Includes a rewrite of the original Perl script, with better documentation and more flexible options, and a C++ interface (usable as a library or app).

hypKNOWsys aims at developing a Java-based workbench for knowledge discovery and knowledge management. Currently, hypKNOWsys has released two intermediate tools: DIAsDEM Workbench (text mining for semantic tagging) and WUMprep (Web mining pre-processing)

JTextPro: A Java-based Text Processing tool that includes sentence boundary detection (using maximum entropy classifier), word tokenization (following Penn conventions), part-of-speech tagging (using CRFTagger), and phrase chunking (using CRFChunker).

CRFTagger: Conditional Random Fields Part-of-Speech (POS) Tagger for English. The model was trained on sections 01..24 of WSJ corpus and using section 00 as the development test set (accuracy of 97.00%). Tagging speed: 500 sentences/s.

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.

Grok is a library of natural language processing components, including support for parsing with categorial grammars and various preprocessing tasks such as part-of-speech tagging, sentence detection, and tokenization.