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The following commit(s) were added to refs/heads/master by this push:
     new 25d517d  Update data-model.html
25d517d is described below

commit 25d517ddf3abf8613cba81a80b28a5fdafa0a054
Author: Aaron Radzinski <[email protected]>
AuthorDate: Wed Jul 28 13:32:47 2021 -0700

    Update data-model.html
---
 data-model.html | 23 ++++++++---------------
 1 file changed, 8 insertions(+), 15 deletions(-)

diff --git a/data-model.html b/data-model.html
index 14cf1ec..f21945f 100644
--- a/data-model.html
+++ b/data-model.html
@@ -473,7 +473,7 @@ intents:
         </div>
     </section>
     <section id="ne">
-        <h2 class="section-sub-title">Named Entities <a href="#"><i 
class="top-link fas fa-fw fa-angle-double-up"></i></a></h2>
+        <h2 class="section-title">Named Entities <a href="#"><i 
class="top-link fas fa-fw fa-angle-double-up"></i></a></h2>
         <p>
             Named entity, also known as a model element or a token, is one of 
the main a components defined by the NLPCraft data model.
             A named entity is one or more individual words that have a 
consistent semantic meaning and typically denote a
@@ -522,34 +522,26 @@ intents:
         </table>
         <p>
             In most cases named entities will have associated <em>normalized 
value</em>. It is especially important for named entities that have many
-            different notational forms such as time and date, currency, 
geographical locations, etc. For example, <code>New York</code>,
+            notational forms such as time and date, currency, geographical 
locations, etc. For example, <code>New York</code>,
             <code>New York City</code> and <code>NYC</code> all refer to the 
same "New York City, NY USA" location which is a standard normalized form.
         </p>
         <p>
-            The process of detecting named entities is called Named Entity 
Recognition (NER). There are many
-            different ways of how a certain named entity can be detected: 
through list of synonyms, by name, rule-based or by using
+            The process of detecting named entities is called Named Entity 
Recognition (NER). There are many ways of how a certain named entity can be 
detected: through list of synonyms, by name, rule-based or by using
             statistical techniques like neural networks with large corpus of 
predefined data. NLPCraft natively supports synonym-based
-            named entities definition as well as the ability to compose 
compose new named entities through powerful <a 
href="/intent-matching.html">Intent Definition Language</a> (IDL)
-            combining other named entities including named entities from 
external projects such OpenNLP, spaCy or Stanford CoreNLP.
+            named entities definition as well as the ability to compose new 
named entities through powerful <a href="/intent-matching.html">Intent 
Definition Language</a> (IDL)
+            combining other named entities including named entities from
+            <a href="/integrations.html">external project</a> such OpenNLP, 
spaCy or Stanford CoreNLP.
         </p>
         <p>
             Named entities allow you to abstract from basic linguistic forms 
like nouns and verbs to deal with the higher level semantic
             abstractions like geographical location or time when you are 
trying to understand the meaning of the sentence.
-            One of the main goals of named entities is to act as an input 
ingredients for intent matching.
-        </p>
-        <p>
-            Read more in-depth about named entities <a 
href="data-model.html">here</a>.
+            One of the main goals of named entities is to act as an input 
ingredients for <a href="/intent-matching.html">intent matching</a>.
         </p>
     </section>
     <section id="elements">
         <h2 class="section-title">Model Elements <a href="#"><i 
class="top-link fas fa-fw fa-angle-double-up"></i></a></h2>
         <p>
             Data model element defines a named entity that will be detected in 
the user input.
-            A model element typically is one or more individual words that 
have a consistent semantic meaning and typically denote a
-            real-world object, such as persons, locations, number, date and 
time, organizations, products, etc. Such
-            object can be abstract or have a physical existence.
-        </p>
-        <p>
             Model element is an implementation of <a target="javadoc" 
href="/apis/latest/org/apache/nlpcraft/model/NCElement.html">NCElement</a>
             interface. <a target="javadoc" 
href="/apis/latest/org/apache/nlpcraft/model/NCModel.html">NCModel</a> provides
             its elements via <a target="javadoc" 
href="/apis/latest/org/apache/nlpcraft/model/NCModelView.html#getElements()">getElements()</a>
 method.
@@ -2817,6 +2809,7 @@ intents:
         <li><a href="#dataflow">Model Dataflow</a></li>
         <li><a href="#lifecycle">Model Lifecycle</a></li>
         <li><a href="#config">Model Configuration</a></li>
+        <li><a href="#ne">Named Entities</a></li>
         <li><a href="#elements">Model Elements</a></li>
         <li><a href="#dsl">IDL Expression</a></li>
         <li><a href="#programmable_ners">Programmable NERs</a></li>

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