PUBLIC MARKS with tag uima

Unstructured Information Management applications are software systems that analyze large volumes of unstructured information in order to discover knowledge that is relevant to an end user. UIMA is a framework and SDK for developing such applications. An example UIM application might ingest plain text and identify entities, such as persons, places, organizations; or relations, such as works-for or located-at. UIMA enables such an application to be decomposed into components, for example "language identification" -> "language specific segmentation" -> "sentence boundary detection" -> "entity detection (person/place names etc.)". Each component must implement interfaces defined by the framework and must provide self-describing metadata via XML descriptor files. The framework manages these components and the data flow between them. Components are written in Java or C ; the data that flows between components is designed for efficient mapping between these languages. UIMA additionally provides capabilities to wrap components as network services, and can scale to very large volumes by replicating processing pipelines over a cluster of networked nodes. Apache UIMA is an Apache-licensed open source implementation of the UIMA specification (that specification is, in turn, being developed concurrently by a technical committee within OASIS , a standards organization). We invite and encourage you to participate in both the implementation and specification efforts.

OpenNLP is an organizational center for open source projects related to natural language processing. Its primary role is to encourage and facilitate the collaboration of researchers and developers on such projects. Click here to see the current list of OpenNLP projects. We'll also try to keep a fairly up-to-date list of useful links related to NLP software in general. OpenNLP also hosts a variety of java-based NLP tools which perform sentence detection, tokenization, pos-tagging, chunking and parsing, named-entity detection, and coreference using the OpenNLP Maxent machine learning package. To start using these tools download the latest release here, and check out the OpenNLP Tools API. For the latest news about these tools and to participate in discussions, check out OpenNLP's Sourceforge project page.