WIP.
diff --git a/_includes/left-side-menu.html b/_includes/left-side-menu.html
index 518b047..0516699 100644
--- a/_includes/left-side-menu.html
+++ b/_includes/left-side-menu.html
@@ -16,7 +16,7 @@
-->
<ul class="side-nav">
- <li class="side-nav-title">Developer Guide</li>
+ <li class="side-nav-title">Introduction</li>
<li>
{% if page.id == "overview" %}
<a class="active" href="/docs.html">Overview</a>
@@ -25,31 +25,50 @@
{% endif %}
</li>
<li>
- {% if page.id == api-review" %}
- <a class="active" href="/api-review.html">API review</a>
+ {% if page.id == "installation" %}
+ <a class="active" href="/installation.html">Installation</a>
{% else %}
- <a href="/api-review.html">API review</a>
+ <a href="/installation.html">Installation</a>
{% endif %}
</li>
<li>
+ {% if page.id == "installation" %}
+ <a class="active" href="/first-example.html">First Example</a>
+ {% else %}
+ <a href="/first-example.html">First Example</a>
+ {% endif %}
+ </li>
+
+ <li class="side-nav-title">Built-in Components</li>
+ <li>
{% if page.id == "semantic" %}
- <a class="active" href="/semantic.html">Semantic parser</a>
+ <a class="active" href="/semantic.html">Semantic Parser</a>
{% else %}
- <a href="/semantic.html">Semantic parser</a>
+ <a href="/semantic.html">Semantic Parser</a>
{% endif %}
</li>
<li>
- {% if page.id == "built-components" %}
- <a class="active" href="/built-components.html">Built components</a>
+ {% if page.id == "built-in-components" %}
+ <a class="active" href="/built-in-components.html">Built-in Components</a>
{% else %}
- <a href="/built-components.html">Built components</a>
+ <a href="/built-in-components.html">Built-in Components</a>
{% endif %}
</li>
+
+ <li class="side-nav-title">Developer Guide</li>
<li>
- {% if page.id == "built-components" %}
- <a class="active" href="/custom-components.html">Custom components</a>
+ {% if page.id == api-review" %}
+ <a class="active" href="/api-review.html">API Review</a>
{% else %}
- <a href="/custom-components.html">Custom components</a>
+ <a href="/api-review.html">API Review</a>
+ {% endif %}
+ </li>
+
+ <li>
+ {% if page.id == "custom-components" %}
+ <a class="active" href="/custom-components.html">Custom Components</a>
+ {% else %}
+ <a href="/custom-components.html">Custom Components</a>
{% endif %}
</li>
<li>
@@ -66,13 +85,7 @@
<a href="/short-term-memory.html">Short-Term Memory</a>
{% endif %}
</li>
- <li>
- {% if page.id == "installation" %}
- <a class="active" href="/installation.html">Installation</a>
- {% else %}
- <a href="/installation.html">Installation</a>
- {% endif %}
- </li>
+
<li class="side-nav-title">Examples</li>
<li>
{% if page.id == "calculator" %}
diff --git a/api-review.html b/api-review.html
index ae557d0..131bc52 100644
--- a/api-review.html
+++ b/api-review.html
@@ -1,7 +1,7 @@
---
active_crumb: Docs
layout: documentation
-id: overview
+id: api-review
---
<!--
@@ -23,10 +23,10 @@
<div class="col-md-8 second-column">
<section id="overview">
- <h2 class="section-title">Library API review <a href="#"><i class="top-link fas fa-fw fa-angle-double-up"></i></a></h2>
+ <h2 class="section-title">API review <a href="#"><i class="top-link fas fa-fw fa-angle-double-up"></i></a></h2>
<p>
- NlpCraft library is based on two main concepts <code>Model</code> and <code>Client</code>
+ NLPCraft library is based on two main concepts <code>Data Model</code> and <code>Client</code>
which have API representations
<a href="apis/latest/org/apache/nlpcraft/NCModel.html">NCModel</a> and
<a href="apis/latest/org/apache/nlpcraft/NCModelClient.html">NCModelClient</a>.
@@ -37,10 +37,10 @@
<ul>
<li>
- <code>Model</code> is domain specific object which responsible for user input interpretation.
+ <code>Data Model</code> is domain specific object which responsible for user input interpretation.
</li>
<li>
- <code>Client</code> is object which allows to communicate with the given model.
+ <code>Client</code> is object which allows to communicate with the given data model.
</li>
</ul>
@@ -59,11 +59,10 @@
// Clears dialog session for user with ID "userId".
client.clearDialog("userId")
</pre>
-
</section>
<section id="model">
- <h2 class="section-title">Model responsibility overview<a href="#"><i class="top-link fas fa-fw fa-angle-double-up"></i></a></h2>
+ <h2 class="section-title">Data Model responsibility<a href="#"><i class="top-link fas fa-fw fa-angle-double-up"></i></a></h2>
<p>
Let's start with terminology and describe the system work workflow.
</p>
@@ -102,13 +101,13 @@
but it can be more flexible.
Parameters extracted from user text input are passed into callback methods.
These methods execution results are provided to user as answer on his request.
- <code>Intent</code> callbacks are methods defined in <code>Model</code> class annotated by
+ <code>Intent</code> callbacks are methods defined in <code>Data Model</code> class annotated by
<code>intent</code> rules via <a href="intent-matching.html">IDL</a>.
</li>
</ul>
<p>
- <code>Model</code> must be able to do tree following things:
+ <code>Data Model</code> must be able to do tree following things:
</p>
<ul>
@@ -194,7 +193,7 @@
</section>
<section id="client">
- <h2 class="section-title">Client responsibility overview<a href="#"><i class="top-link fas fa-fw fa-angle-double-up"></i></a></h2>
+ <h2 class="section-title">Client responsibility<a href="#"><i class="top-link fas fa-fw fa-angle-double-up"></i></a></h2>
<p>
Client which is represented as <a href="apis/latest/org/apache/nlpcraft/NCModelClient.html">NCModelClient</a>
@@ -233,7 +232,7 @@
<h2 class="section-title">Model configuration <a href="#"><i class="top-link fas fa-fw fa-angle-double-up"></i></a></h2>
<p>
- Model configuration <a href="apis/latest/org/apache/nlpcraft/NCModelConfig.html">NCModelConfig</a> represents set of model parameter values.
+ Data Model configuration <a href="apis/latest/org/apache/nlpcraft/NCModelConfig.html">NCModelConfig</a> represents set of model parameter values.
Its properties are described below.
</p>
<ul>
@@ -268,7 +267,7 @@
<li>
<code>Token parser</code> represented as <a href="apis/latest/org/apache/nlpcraft/NCTokenParser.html">NCTokenParser</a>.
Mandatory pipeline component, it is required for parsing plain text, user input, and split this text
- into tokens list. NlpCraft provides default EN implementation of token parser.
+ into tokens list. NLPCraft provides default EN implementation of token parser.
Also, project contain various examples for <a href="examples/light_switch_fr.html">French</a> and
<a href="examples/light_switch_ru.html">Russia</a> languages.
</li>
@@ -276,7 +275,7 @@
<code>Tokens enrichers</code> represented as <a href="apis/latest/org/apache/nlpcraft/NCTokenEnricher.html">NCTokenEnricher</a> optional list.
Tokens enricher is component which allows to add additional properties to prepared tokens,
like part of speech, quote, stop-words flags or any other.
- NlpCraft provides default set of EN tokens enrichers implementations.
+ NLPCraft provides default set of EN tokens enrichers implementations.
</li>
<li>
<code>Tokens validators</code> represented as <a href="apis/latest/org/apache/nlpcraft/NCTokenValidator.html">NCTokenValidator</a> optional list.
@@ -287,7 +286,7 @@
<code>Entity parsers</code> represented as <a href="apis/latest/org/apache/nlpcraft/NCEntityParser.html">NCEntityParser</a> mandatory list.
At least one entity parser must be defined. Having prepared tokens as input,
each entity parser tries to find user defined named entities.
- NlpCraft provides wrappers for named-entity recognition components of OpenNLP and Stanford libraries.
+ NLPCraft provides wrappers for named-entity recognition components of OpenNLP and Stanford libraries.
</li>
<li>
<code>Entity enrichers</code> represented as <a href="apis/latest/org/apache/nlpcraft/NCEntityEnricher.html">NCEntityEnricher</a> optional list.
@@ -330,7 +329,7 @@
<p>
This flexible system allows to create any pipelines on any language.
- You can collect NlpCraft predefined components, write your own and easy reuse custom components.
+ You can collect NLPCraft predefined components, write your own and easy reuse custom components.
</p>
</section>
diff --git a/built-components.html b/built-in-components.html
similarity index 95%
rename from built-components.html
rename to built-in-components.html
index 03de60f..a3cd108 100644
--- a/built-components.html
+++ b/built-in-components.html
@@ -1,7 +1,7 @@
---
active_crumb: Docs
layout: documentation
-id: overview
+id: built-in-components
---
<!--
@@ -23,18 +23,18 @@
<div class="col-md-8 second-column">
<section id="overview">
- <h2 class="section-title">Built components <a href="#"><i class="top-link fas fa-fw fa-angle-double-up"></i></a></h2>
+ <h2 class="section-title">Built-in components <a href="#"><i class="top-link fas fa-fw fa-angle-double-up"></i></a></h2>
<p>
Model <a href="apis/latest/org/apache/nlpcraft/NCPipeline.html">NCPipeline</a>
is base model element. It defines chain of components traits which are responsible for sentence processing.
- Some built implementations of these traits are described below.
+ Some built-in implementations of these traits are described below.
</p>
<div class="bq info">
- <p><b>Built component licenses.</b></p>
+ <p><b>Built-in component licenses.</b></p>
<p>
- All built components which are based on <a href="https://nlp.stanford.edu/">Stanford NLP</a> models and classes
+ All built-in components which are based on <a href="https://nlp.stanford.edu/">Stanford NLP</a> models and classes
are provided with <a href="http://www.gnu.org/licenses/gpl-2.0.html">GNU General Public License</a>.
Look at Stanford NLP <a href="https://nlp.stanford.edu/software/">Software</a> page.
All such components are placed in special project module <code>nlpcraft-stanford</code>.
@@ -45,7 +45,7 @@
<ul>
<li>
<a href="apis/latest/org/apache/nlpcraft/NCTokenParser.html">NCTokenParser</a>.
- There are provided two built implementations, both of them are for English language.
+ There are provided two built-in implementations, both of them are for English language.
<ul>
<li>
<a href="apis/latest/org/apache/nlpcraft/nlp/parsers/NCOpenNLPTokenParser.html">NCOpenNLPTokenParser</a>.
@@ -61,7 +61,7 @@
<li>
<a href="apis/latest/org/apache/nlpcraft/NCTokenEnricher.html">NCTokenEnricher</a>.
- There are provided a number of built implementations, all of them are for English language.
+ There are provided a number of built-in implementations, all of them are for English language.
<ul>
<li>
<a href="apis/latest/org/apache/nlpcraft/nlp/enrichers/NCOpenNLPLemmaPosTokenEnricher.html">NCOpenNLPLemmaPosTokenEnricher</a> -
@@ -107,7 +107,7 @@
<li>
<a href="apis/latest/org/apache/nlpcraft/NCEntityParser.html">NCEntityParser</a>.
- There are provided a number of language independent built implementations.
+ There are provided a number of language independent built-in implementations.
They use their own models which can be on different languages.
<ul>
<li>
@@ -189,7 +189,7 @@
</li>
</ul>
- <p><b>Example with pipeline configured by built components:</b></p>
+ <p><b>Example with pipeline configured by built-in components:</b></p>
<pre class="brush: scala, highlight: [2, 6, 7, 12, 13, 14, 15]">
val pipeline =
diff --git a/custom-components.html b/custom-components.html
index 51c6f67..1905349 100644
--- a/custom-components.html
+++ b/custom-components.html
@@ -1,7 +1,7 @@
---
active_crumb: Docs
layout: documentation
-id: overview
+id: custom-components
---
<!--
@@ -26,7 +26,7 @@
<h2 class="section-title">Custom components <a href="#"><i class="top-link fas fa-fw fa-angle-double-up"></i></a></h2>
<p>
- NlpCraft provides a numeric of useful built components for English language.
+ NLPCraft provides a numeric of useful built-in components for English language.
You can use them to prepare <a href="apis/latest/org/apache/nlpcraft/NCPipeline.html">NCPipeline</a>
for your <a href="apis/latest/org/apache/nlpcraft/NCModel.html">NCModel</a>.
You also can use provided wrappers on <a href="https://opennlp.apache.org/">Apache OpenNLP</a> and
@@ -170,7 +170,7 @@
<p>
Most important component which finds user specific data.
These defined entities are input for <a href="intent-matching.html">Intent matching</a> conditions.
- If built <a href="apis/latest/org/apache/nlpcraft/nlp/parsers/NCSemanticEntityParser.html">NCSemanticEntityParser</a>
+ If built-in <a href="apis/latest/org/apache/nlpcraft/nlp/parsers/NCSemanticEntityParser.html">NCSemanticEntityParser</a>
is not enough, you can implement your own NER searching here.
There is point for potential integrations with neural networks or any other solutions which
help you find and mark your domain specific named entities.
diff --git a/examples/calculator.html b/examples/calculator.html
index 081f55c..9695809 100644
--- a/examples/calculator.html
+++ b/examples/calculator.html
@@ -163,7 +163,7 @@
<code>Line 12</code> defines arithmetic operations map with notations as keys and functions definitions as values.
</li>
<li>
- <code>Line 14</code> defines model pipeline based on three built components.
+ <code>Line 14</code> defines model pipeline based on three built-in components.
<code>Line 21</code> defines Stanford token parser <code>NCStanfordNLPTokenParser</code>
(we use Stanford NLP components in this example).
</li>
diff --git a/examples/light_switch_fr.html b/examples/light_switch_fr.html
index 49241b2..7e65f24 100644
--- a/examples/light_switch_fr.html
+++ b/examples/light_switch_fr.html
@@ -241,7 +241,7 @@
</li>
</ul>
</section>
- <section id="code">
+ <section id="custom">
<h2 class="section-title">Custom Components <a href="#"><i class="top-link fas fa-fw fa-angle-double-up"></i></a></h2>
<p>
Open <code>src/main/scala/demo/nlp/token/parser/<b>NCFrTokenParser.scala</b></code> file and replace its content with the following code:
@@ -479,6 +479,7 @@
<li><a href="#new_project">New Project</a></li>
<li><a href="#model">Data Model</a></li>
<li><a href="#code">Model Class</a></li>
+ <li><a href="#custom">Custom Components</a></li>
<li><a href="#testing">Testing</a></li>
{% include quick-links.html %}
</ul>
diff --git a/examples/light_switch_ru.html b/examples/light_switch_ru.html
index 39f1f9e..72c4d52 100644
--- a/examples/light_switch_ru.html
+++ b/examples/light_switch_ru.html
@@ -239,7 +239,7 @@
</ul>
</section>
- <section id="code">
+ <section id="custom">
<h2 class="section-title">Custom Components <a href="#"><i class="top-link fas fa-fw fa-angle-double-up"></i></a></h2>
<p>
@@ -473,6 +473,7 @@
<li><a href="#new_project">New Project</a></li>
<li><a href="#model">Data Model</a></li>
<li><a href="#code">Model Class</a></li>
+ <li><a href="#custom">Custom Components</a></li>
<li><a href="#testing">Testing</a></li>
{% include quick-links.html %}
</ul>
diff --git a/examples/time.html b/examples/time.html
index 1fe0dd8..9e991fb 100644
--- a/examples/time.html
+++ b/examples/time.html
@@ -225,14 +225,14 @@
<code>Line 20</code> creates model configuration with most default parameters.
</li>
<li>
- <code>Line 21</code> creates pipeline based on built components.
+ <code>Line 21</code> creates pipeline based on built-in components.
<ul>
- <li>This pipeline is based on built EN semantic entity enricher configured with <code>time_model.yaml</code>.</li>
+ <li>This pipeline is based on built-in EN semantic entity enricher configured with <code>time_model.yaml</code>.</li>
<li>Also there is entity parser <code>NCOpenNLPEntityParser</code>
configured by <code>opennlp/en-ner-location.bin</code> for GEO locations detection.
</li>
</ul>
- Look at these built components documentation for more details.
+ Look at these built-in components documentation for more details.
</li>
<li>
<code>Lines 56 and 57</code> annotate intent <code>intent2</code> and its callback method <code>onRemoteMatch()</code>.
diff --git a/installation.html b/installation.html
index 00085ca..89f49c6 100644
--- a/installation.html
+++ b/installation.html
@@ -31,11 +31,16 @@
<li>If you <a href="/download.html">downloaded</a> binary ZIP archive -
<a target="asf" href="https://www.apache.org/dyn/closer.cgi#verify">verify</a> it and unzip it.
</li>
- <li>If you <a href="/download.html">cloned</a> GitHub repository or downloaded source archive
- <code>sbt clean compile</code> to build it.
+ <li>If you <a href="/download.html">cloned</a> GitHub repository or downloaded source archive compile
+ it via <code>SBT</code> command.
+ <pre class="brush: scala, highlight: []">
+ $ sbt clean compile
+ </pre>
</li>
- <li>Also you can use <code>maven</code> command <code>mvn -B clean package -P stanford-core,examples</code>
- and get same result.
+ <li>Also you can use <code>maven</code> command and get same result.
+ <pre class="brush: scala, highlight: []">
+ $ mvn -B clean package -P stanford-core,examples
+ </pre>
</li>
</ul>
<p>
@@ -47,9 +52,6 @@
</p>
<p>
Starting with version <b>1.0.0</b> NLPCraft requires JDK 11+ and Scala 3.1.3.<br/>
- Starting with version <b>0.9.0</b> NLPCraft requires JDK 11+ and Scala 2.13.<br/>
- Starting with version <b>0.7.0</b> NLPCraft requires JDK 11+ and Scala 2.12.<br/>
- Prior versions supported JDK 8 and Scala 2.12.
</p>
</div>
</section>
@@ -71,24 +73,10 @@
)
</pre>
- <ul>
- <li>
- Now you can use <code>NlpCraft</code> library in <code>Your project</code>.
- </li>
- <li>
- You can use <a href="https://www.scala-sbt.org/">SBT</a> or
- <a href="https://maven.apache.org/">Maven</a>
- systems depending on your requirements via links
- to <a href="https://search.maven.org/">Maven Central</a>.
- </li>
- <li>
- You also can build <code>NlpCraft</code> library source code and use references on jar files via
- <a href="https://ant.apache.org/">Ant</a> or any another way.
- </li>
- </ul>
+ <p><b>NOTE: </b>use the latest versions of Scala and ScalaTest.</p>
<p>
- Go to Examples section to start work with concrete example.
+ Go to <a href="first-example.html">First example</a> section to look at concrete example.
</p>
</section>
</div>
diff --git a/semantic.html b/semantic.html
index 7528397..daad390 100644
--- a/semantic.html
+++ b/semantic.html
@@ -30,7 +30,7 @@
<a href="apis/latest/org/apache/nlpcraft/nlp/parsers/NCSemanticEntityParser.html">NCSemanticEntityParser</a>
is the implementation of <a href="apis/latest/org/apache/nlpcraft/NCEntityParser.html">NCEntityParser</a>,
which in turn is component of the model pipeline <a href="apis/latest/org/apache/nlpcraft/NCPipeline.html">NCPipeline</a>.
- In spite of that it is just one of defined in NlpCraft built component, it deserves a special mention.
+ In spite of that it is just one of defined in NLPCraft built-in component, it deserves a special mention.
This parser provides simple but very powerful way to find domain specific data in the input text.
It defines list of <a href="apis/latest/org/apache/nlpcraft/nlp/parsers/NCSemanticElement.html">NCSemanticElement</a>
which are represent <a href="https://en.wikipedia.org/wiki/Named-entity_recognition">Named entities</a>.
@@ -99,7 +99,7 @@
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 new named entities through powerful <a href="/intent-matching.html">Intent Definition Language</a> (IDL)
combining other named entities including named entities from
- such OpenNLP, or Stanford CoreNLP, look at the <a href="built-components.html">Built component</a> chapter.
+ such OpenNLP, or Stanford CoreNLP, look at the <a href="built-in-components.html">Built component</a> chapter.
</p>
<p>
Named entities allow you to abstract from basic linguistic forms like nouns and verbs to deal with the higher level semantic
