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https://issues.apache.org/jira/browse/STANBOL-733?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Sebastian Schaffert updated STANBOL-733:
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Attachment: srfgkmt-stanbol-nlp.zip
A patch containing NLP enhancement engines for Apache Stanbol addressing the
goals mentioned in the issue. This excludes all data files, they can be found
at https://www.dropbox.com/home/Public/stanbol
> Stanbol NLP processing
> ----------------------
>
> Key: STANBOL-733
> URL: https://issues.apache.org/jira/browse/STANBOL-733
> Project: Stanbol
> Issue Type: New Feature
> Components: Enhancer
> Reporter: Rupert Westenthaler
> Attachments: srfgkmt-stanbol-nlp.zip
>
>
> This issue covers the NLP processing components as discussed in
> http://markmail.org/message/qxusiup3mim2lhpx
> Goals
> =====
> 1. provide a modular infrastructure for NLP-related things
> Many tasks in NLP can be computationally intensive, and there is no "one fits
> all" NLP approach when analysing text. Therefore, we wanted to have a NLP
> infrastructure that can be configured and wired together as needed for the
> specific use case, with several specialised modules that can build upon each
> other but many of which are optional.
> 2. provide a unified data model for representing NLP text annotations
> In many szenarios, it will be necessary to implement custom engines building
> on
> the results of a previous "generic" analysis of the text (e.g. POS tagging and
> chunking). For example, in a project we are identifying so-called "noun
> phrases", use a lemmatizer to build the ground form, then convert this to
> singular nominative form to have a gramatically correct label to use in a tag
> cloud. Most of this builds on generic NLP functionality, but the last step is
> very specific to the use case.
> Therefore, we wanted also to implement a generic NLP data model that allows
> representing text annotations attached to individual words or also to spans of
> words.
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