Author: agruber
Date: Fri Sep 23 08:22:05 2011
New Revision: 1174583
URL: http://svn.apache.org/viewvc?rev=1174583&view=rev
Log:
updated costumvocabulary desc with keyword engine
Modified:
incubator/stanbol/site/trunk/content/stanbol/docs/trunk/customvocabulary.mdtext
Modified:
incubator/stanbol/site/trunk/content/stanbol/docs/trunk/customvocabulary.mdtext
URL:
http://svn.apache.org/viewvc/incubator/stanbol/site/trunk/content/stanbol/docs/trunk/customvocabulary.mdtext?rev=1174583&r1=1174582&r2=1174583&view=diff
==============================================================================
---
incubator/stanbol/site/trunk/content/stanbol/docs/trunk/customvocabulary.mdtext
(original)
+++
incubator/stanbol/site/trunk/content/stanbol/docs/trunk/customvocabulary.mdtext
Fri Sep 23 08:22:05 2011
@@ -4,7 +4,7 @@ The ability to work with custom vocabula
For text enhancement and linking to external sources, the Entityhub component
of Apache Stanbol allows to work with local indexes of datasets for several
reasons:
-- do not want to rely on internet connectivity to these services, thus working
offline with a huge set of enties
+- do not want to rely on internet connectivity to these services, thus working
offline with a huge set of entities
- want to manage local updates of these public repositories and
- want to work with local resources only, such as your LDAP directory or a
specific and private enterprise vocabulary of a specific domain.
@@ -22,7 +22,7 @@ Stanbol provides the machinery to start
The indexing tool provides a default configuration for creating a SOLr index
of RDF files (e.g. a SKOS export of a thesaurus or a set of foaf files).
-If not yet built during the Stanbol build process of the entityhub call
+If not yet built during the Stanbol build process of the Entityhub call
mvn install
@@ -45,7 +45,7 @@ Initialize the tool with
You will get a directory with the default configuration files, one for the
sources and a distribution directory for the resulting files. Make sure, that
you adapt the default configuration with at least
-- the id/name and licence information of your data and
+- the id/name and license information of your data and
- namespaces and properties mapping you want to include to the index (see
example of a [mappings.txt](examples/anl-mappings.txt) including default and
specific mappings for one dataset)
Then, copy your source files into the respective directory
<code>indexing/resources/rdfdata</code>. Several standard formats for RDF,
multiple files and archives of them are supported.
@@ -59,60 +59,62 @@ Then, you can start the index by running
Depending on your hardware and on complexity and size of your sources, it may
take several hours to built the index. As a result, you will get an archive of
a [SOLr](http://lucene.apache.org/solr/) index together with an OSGI bundle to
work with the index in Stanbol.
-**Step 3 : Initialise the index within Stanbol**
+**Step 3 : Initialize the index within Stanbol**
At your running Stanbol instance, copy the ZIP archive into
<code>{root}/sling/datafiles</code>. Then, at the "Bundles" tab of the
administration console add and start the
<code>org.apache.stanbol.data.site.{name}-{version}.jar</code>.
### B. Configure and use the index with enhancement engines
-Before you can make use of the custom vocabulary you need to decide, which
kind of enhancements you want to support. If your enhancements are
NamedEntities in its more strict sense (Persons, Locations, Organizations),
then you can may use the standard NER engine together with its
EntityLinkingEngine to configure the destination of your links.
+Before you can make use of the custom vocabulary you need to decide, which
kind of enhancements you want to support. If your enhancements are Named
Entities in its strict sense (Persons, Locations, Organizations), then you may
use the standard NER engine together with its EntityLinkingEngine to configure
the destination of your links.
-In such cases, where you want to match all kinds of named entities and
concepts from your custom vocabulary, you should work with the
TaxonomyLinkingEngine to both, find occurrences and to link them to custom
entities. In this case, you'll get only results, if there is a match, while in
the case above, you even get entities, where you don't find exact links. This
approach will have its advantages when you need to have a high recall rate on
your custom entities.
+In cases, where you want to match all kinds of named entities and concepts
from your custom vocabulary, you should work with the
[KeywordLinkingEngine](enhancer/engines/keywordlinkingengine.html) to both,
find occurrences and to link them to custom entities. In this case, you'll get
only results, if there is a match, while in the case above, you even get
entities, where you don't find exact links. This approach will have its
advantages when you need to have a high recall rate on your custom entities.
In the following the configuration options are described briefly.
-**Use the TaxonomyLinkingEngine only**
+**Use the KeywordLinkingEngine only**
-(1) To make sure, that the enhancement process uses the TaxonomyEngine only,
deactivate the "standard NLP" enhancement engines, especially the
NamedEntityExtractionEnhancementEngine (NER) and the EntityLinkingEngine before
to work with the TaxonomyLinkingEngine.
+(1) To make sure, that the enhancement process uses the KeywordLinkingEngine
only, deactivate the "standard NLP" enhancement engines, especially the
NamedEntityExtractionEnhancementEngine (NER) and the EntityLinkingEngine before
to work with the TaxonomyLinkingEngine.
-(2) Open the configuration console at
http://localhost:8080/system/console/configMgr and navigate to the
TaxonomyLinkingEngine. Its main options are configurable via the UI.
+(2) Open the configuration console at
http://localhost:8080/system/console/configMgr and navigate to the
KeywordLinkingEngine. Its main options are configurable via the UI.
- Referenced Site: {put the id/name of your index}
-- Label Field: {the property to search for}
-- Use Simple Tokenizer: {deactivate to use language specific tokenizers}
+- Label Field: {the property to search for}
+- Type Field: {types of matched entries}
+- Redirect Field: {redirection links}
+- Redirect Mode: {ignore, follow, add values}
- Min Token Length: {set minimal token length}
-- Use Chunker: {disable/enable language specific chunkers}
- Suggestions: {maximum number of suggestions}
-- Number of Required Tokens: {minimal required tokens}
+- Languages: {languages to use}
-*For further details please on the engine and its configuration please refer
to the according README at
<code>{root}/stanbol/enhancer/engines/taxonomylinking/</code>.* (TODO: create
the Readme)
+*Full details on the engine and its configuration are available
[here](enhancer/engines/keywordextraction.html).*
-**Use several instances of the TaxonomyLinkingEngine**
+**Use several instances of the KeywordLinkingEngine**
-To work at the same time with different instances of the TaxonomyLinkingEngine
can be useful in cases, where you have two or more distinct custom
vocabularies/indexes and/or if you want to combine your specific domain
vocabulary with general purpose datasets such as dbpedia or others.
+To work at the same time with different instances of the KeywordLinkingEngine
can be useful in cases, where you have two or more distinct custom
vocabularies/indexes and/or if you want to combine your specific domain
vocabulary with general purpose datasets such as dbpedia or others.
-**Use the TaxonomyLinkingEngine together with the NER engine and the
EntityLinkingEngine**
+**Use the KeywordLinkingEngine together with the NER engine and the
EntityLinkingEngine**
-If your text corpus contains and you are interested in both, generic
NamedEntities and custom thesaurus you may use (TODO)
+If your text corpus contains common entities and enterprise specific as well
and you are interested getting enhancements for both, you may also use the
KeywordLinkingEngine for your custom thesaurus and the NERengine together with
the EntityLinkingEngine targeting at e.g. dbpedia at the same time.
-## Specific Examples
+## Examples
You can find guidance for the following indexers in the README files at
<code>{root}/entityhub/indexing/{name-for-indexer}</code>
-- [DBpedia](http://dbpedia.org/) dataset (Wikipedia data)
+- [dbpedia](http://dbpedia.org/) dataset (Wikipedia data)
+ For dbpedia, there is also a
[script](http://svn.apache.org/repos/asf/incubator/stanbol/trunk/entityhub/indexing/dbpedia/fetch_prepare.sh)
available, which helps in generating your own dbpedia index.
- [geonames.org](http://www.geonames.org) dataset (geolocation data)
- [DBLP](http://dblp.uni-trier.de/) dataset (scientific bibliography data)
-## Demos and Ressources
+## Demos and Resources
- The full [demo](http://dev.iks-project.eu:8081/) installation of Stanbol is
configured to also work with an environmental thesaurus - if you test it with
unstructured text from the domain, you should get enhancements with additional
results for specific "concepts".
- Download custom test indexes and installer bundles for Stanbol from
[here](http://dev.iks-project.eu/downloads/stanbol-indices/) (e.g. for GEMET
environmental thesaurus, or a big dbpedia index).
-- Another concrete example with metadata from the Austrian National Library is
described (TODO: link) here.
+- A very concrete example using metadata from the Austrian National Library is
described
[here](http://blog.iks-project.eu/using-custom-vocabularies-with-apache-stanbol/).
