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_sources/introduction.rst.txt

@@ -22,16 +22,3 @@ networks and their automated extraction.
 
 .. _LabatutAndBost2019: https://arxiv.org/abs/1907.02704
 
-
-Target Audience and Intended Usage
-==================================
-
-Renard can be used by digital humanities researchers to extract
-character networks, for example to bring additional information when
-performing literary analysis.
-
-Renard can also be used by Natural Language Processing (NLP)
-researchers and practitioners to extract graph representations of
-texts, in order to use these as inputs to downstream NLP tasks. Graphs
-embedding algorithms such as Graph2Vec may be used on these graphs to
-derive a vectorial representation of texts.

_sources/pipeline.rst.txt

@@ -22,7 +22,7 @@ document. Here is a simple example:
        [
            NLTKTokenizer(),
            NLTKNamedEntityRecognizer(),
-           GraphRulesCharacterUnifier(min_appearances=10),
+           GraphRulesCharacterUnifier(min_appearance=10),
            CoOccurrencesGraphExtractor(co_occurrences_dist=25)
        ]
    )
@@ -55,7 +55,7 @@ to compute them yourself:
    pipeline = Pipeline(
        [
            NLTKNamedEntityRecognizer(),
-           GraphRulesCharacterUnifier(min_appearances=10),
+           NaiveCharactersExtractor(min_appearance=10),
            CoOccurrencesGraphExtractor(co_occurrences_dist=25)
        ]
    )
@@ -64,13 +64,6 @@ to compute them yourself:
    out = pipeline(text, tokens=my_tokenization_function(text))
 
 
-In that case, the ``tokens`` requirements is fulfilled at run time. If
-you don't pass the parameter, Renard will throw the following
-exception:
-
->>> ValueError: ["step 1 (NLTKNamedEntityRecognizer) has unsatisfied needs (needs : {'tokens'}, available : {'text'})"]
-
-
 For simplicity, one can use one of the preconfigured pipelines:
 
 .. code-block:: python

_sources/reference.rst.txt

@@ -184,10 +184,3 @@ Plot utils
 
 .. automodule:: renard.plot_utils
    :members:
-
-
-NER utils
----------
-
-.. automodule:: renard.ner_utils
-   :members:

genindex.html

@@ -98,11 +98,9 @@ <h1 id="index">Index</h1>
 <h2 id="_">_</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="reference.html#renard.ner_utils.DataCollatorForTokenClassificationWithBatchEncoding.__call__">__call__() (renard.ner_utils.DataCollatorForTokenClassificationWithBatchEncoding method)</a>
+      <li><a href="reference.html#renard.pipeline.character_unification.GraphRulesCharacterUnifier.__call__">__call__() (renard.pipeline.character_unification.GraphRulesCharacterUnifier method)</a>
 
       <ul>
-        <li><a href="reference.html#renard.pipeline.character_unification.GraphRulesCharacterUnifier.__call__">(renard.pipeline.character_unification.GraphRulesCharacterUnifier method)</a>
-</li>
         <li><a href="reference.html#renard.pipeline.character_unification.NaiveCharacterUnifier.__call__">(renard.pipeline.character_unification.NaiveCharacterUnifier method)</a>
 </li>
         <li><a href="reference.html#renard.pipeline.core.Pipeline.__call__">(renard.pipeline.core.Pipeline method)</a>
@@ -156,13 +154,9 @@ <h2 id="_">_</h2>
         <li><a href="reference.html#renard.pipeline.ner.NEREntity.__hash__">(renard.pipeline.ner.NEREntity method)</a>
 </li>
       </ul></li>
-      <li><a href="reference.html#renard.ner_utils.DataCollatorForTokenClassificationWithBatchEncoding.__init__">__init__() (renard.ner_utils.DataCollatorForTokenClassificationWithBatchEncoding method)</a>
+      <li><a href="reference.html#renard.pipeline.character_unification.Character.__init__">__init__() (renard.pipeline.character_unification.Character method)</a>
 
       <ul>
-        <li><a href="reference.html#renard.ner_utils.NERDataset.__init__">(renard.ner_utils.NERDataset method)</a>
-</li>
-        <li><a href="reference.html#renard.pipeline.character_unification.Character.__init__">(renard.pipeline.character_unification.Character method)</a>
-</li>
         <li><a href="reference.html#renard.pipeline.character_unification.GraphRulesCharacterUnifier.__init__">(renard.pipeline.character_unification.GraphRulesCharacterUnifier method)</a>
 </li>
         <li><a href="reference.html#renard.pipeline.character_unification.NaiveCharacterUnifier.__init__">(renard.pipeline.character_unification.NaiveCharacterUnifier method)</a>
@@ -249,8 +243,6 @@ <h2 id="_">_</h2>
       <li><a href="reference.html#renard.pipeline.core.Pipeline._pipeline_init_steps">_pipeline_init_steps() (renard.pipeline.core.Pipeline method)</a>
 </li>
       <li><a href="reference.html#renard.pipeline.corefs.SpacyCorefereeCoreferenceResolver._spacy_try_infer_spaces">_spacy_try_infer_spaces() (renard.pipeline.corefs.SpacyCorefereeCoreferenceResolver static method)</a>
-</li>
-      <li><a href="reference.html#renard.ner_utils._tokenize_and_align_labels">_tokenize_and_align_labels() (in module renard.ner_utils)</a>
 </li>
   </ul></td>
 </tr></table>
@@ -315,10 +307,6 @@ <h2 id="C">C</h2>
 
 <h2 id="D">D</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
-  <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="reference.html#renard.ner_utils.DataCollatorForTokenClassificationWithBatchEncoding">DataCollatorForTokenClassificationWithBatchEncoding (class in renard.ner_utils)</a>
-</li>
-  </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="reference.html#renard.graph_utils.dynamic_graph_to_gephi_graph">dynamic_graph_to_gephi_graph() (in module renard.graph_utils)</a>
 </li>
@@ -359,10 +347,6 @@ <h2 id="G">G</h2>
 
 <h2 id="H">H</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
-  <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="reference.html#renard.ner_utils.hgdataset_from_conll2002">hgdataset_from_conll2002() (in module renard.ner_utils)</a>
-</li>
-  </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="reference.html#renard.resources.hypocorisms.HypocorismGazetteer">HypocorismGazetteer (class in renard.resources.hypocorisms)</a>
 </li>
@@ -381,10 +365,6 @@ <h2 id="L">L</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="reference.html#renard.graph_utils.layout_with_names">layout_with_names() (in module renard.graph_utils)</a>
-</li>
-  </ul></td>
-  <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="reference.html#renard.ner_utils.load_conll2002_bio">load_conll2002_bio() (in module renard.ner_utils)</a>
 </li>
   </ul></td>
 </tr></table>
@@ -399,8 +379,6 @@ <h2 id="M">M</h2>
 
       <ul>
         <li><a href="reference.html#module-renard.graph_utils">renard.graph_utils</a>
-</li>
-        <li><a href="reference.html#module-renard.ner_utils">renard.ner_utils</a>
 </li>
         <li><a href="reference.html#module-renard.pipeline.preprocessing">renard.pipeline.preprocessing</a>
 </li>
@@ -455,10 +433,6 @@ <h2 id="N">N</h2>
       </ul></li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="reference.html#renard.ner_utils.ner_entities">ner_entities() (in module renard.ner_utils)</a>
-</li>
-      <li><a href="reference.html#renard.ner_utils.NERDataset">NERDataset (class in renard.ner_utils)</a>
-</li>
       <li><a href="reference.html#renard.pipeline.ner.NEREntity">NEREntity (class in renard.pipeline.ner)</a>
 </li>
       <li><a href="reference.html#renard.pipeline.ner.NLTKNamedEntityRecognizer">NLTKNamedEntityRecognizer (class in renard.pipeline.ner)</a>
@@ -560,13 +534,6 @@ <h2 id="R">R</h2>
 
       <ul>
         <li><a href="reference.html#module-renard.graph_utils">module</a>
-</li>
-      </ul></li>
-      <li>
-    renard.ner_utils
-
-      <ul>
-        <li><a href="reference.html#module-renard.ner_utils">module</a>
 </li>
       </ul></li>
       <li>
@@ -576,15 +543,15 @@ <h2 id="R">R</h2>
         <li><a href="reference.html#module-renard.pipeline.preprocessing">module</a>
 </li>
       </ul></li>
-  </ul></td>
-  <td style="width: 33%; vertical-align: top;"><ul>
       <li>
     renard.pipeline.stanford_corenlp
 
       <ul>
         <li><a href="reference.html#module-renard.pipeline.stanford_corenlp">module</a>
 </li>
       </ul></li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
       <li>
     renard.plot_utils
 

index.html

@@ -79,10 +79,7 @@ <h1>Welcome to Renard’s documentation!<a class="headerlink" href="#welcome-to-
 <div class="toctree-wrapper compound">
 <p class="caption" role="heading"><span class="caption-text">Contents:</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="introduction.html">Introduction</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="introduction.html#target-audience-and-intended-usage">Target Audience and Intended Usage</a></li>
-</ul>
-</li>
+<li class="toctree-l1"><a class="reference internal" href="introduction.html">Introduction</a></li>
 <li class="toctree-l1"><a class="reference internal" href="installation.html">Installation</a><ul>
 <li class="toctree-l2"><a class="reference internal" href="installation.html#using-pip">Using Pip</a></li>
 <li class="toctree-l2"><a class="reference internal" href="installation.html#manual-installation">Manual Installation</a></li>

introduction.html

@@ -43,10 +43,7 @@
         </div><div class="wy-menu wy-menu-vertical" data-spy="affix" role="navigation" aria-label="Navigation menu">
               <p class="caption" role="heading"><span class="caption-text">Contents:</span></p>
 <ul class="current">
-<li class="toctree-l1 current"><a class="current reference internal" href="#">Introduction</a><ul>
-<li class="toctree-l2"><a class="reference internal" href="#target-audience-and-intended-usage">Target Audience and Intended Usage</a></li>
-</ul>
-</li>
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Introduction</a></li>
 <li class="toctree-l1"><a class="reference internal" href="installation.html">Installation</a></li>
 <li class="toctree-l1"><a class="reference internal" href="pipeline.html">The Pipeline</a></li>
 <li class="toctree-l1"><a class="reference internal" href="extending.html">Extending Renard</a></li>
@@ -94,18 +91,7 @@ <h1>Introduction<a class="headerlink" href="#introduction" title="Permalink to t
 </ul>
 <p>See <a class="reference external" href="https://arxiv.org/abs/1907.02704">LabatutAndBost2019</a> for a more complete overview of character
 networks and their automated extraction.</p>
-<img alt="_images/pp.svg" src="_images/pp.svg" /><section id="target-audience-and-intended-usage">
-<h2>Target Audience and Intended Usage<a class="headerlink" href="#target-audience-and-intended-usage" title="Permalink to this headline"></a></h2>
-<p>Renard can be used by digital humanities researchers to extract
-character networks, for example to bring additional information when
-performing literary analysis.</p>
-<p>Renard can also be used by Natural Language Processing (NLP)
-researchers and practitioners to extract graph representations of
-texts, in order to use these as inputs to downstream NLP tasks. Graphs
-embedding algorithms such as Graph2Vec may be used on these graphs to
-derive a vectorial representation of texts.</p>
-</section>
-</section>
+<img alt="pp.svg" src="pp.svg" /></section>
 
 
            </div>

pipeline.html

@@ -111,7 +111,7 @@ <h1>The Pipeline<a class="headerlink" href="#the-pipeline" title="Permalink to t
     <span class="p">[</span>
         <span class="n">NLTKTokenizer</span><span class="p">(),</span>
         <span class="n">NLTKNamedEntityRecognizer</span><span class="p">(),</span>
-        <span class="n">GraphRulesCharacterUnifier</span><span class="p">(</span><span class="n">min_appearances</span><span class="o">=</span><span class="mi">10</span><span class="p">),</span>
+        <span class="n">GraphRulesCharacterUnifier</span><span class="p">(</span><span class="n">min_appearance</span><span class="o">=</span><span class="mi">10</span><span class="p">),</span>
         <span class="n">CoOccurrencesGraphExtractor</span><span class="p">(</span><span class="n">co_occurrences_dist</span><span class="o">=</span><span class="mi">25</span><span class="p">)</span>
     <span class="p">]</span>
 <span class="p">)</span>
@@ -140,7 +140,7 @@ <h1>The Pipeline<a class="headerlink" href="#the-pipeline" title="Permalink to t
 <span class="n">pipeline</span> <span class="o">=</span> <span class="n">Pipeline</span><span class="p">(</span>
     <span class="p">[</span>
         <span class="n">NLTKNamedEntityRecognizer</span><span class="p">(),</span>
-        <span class="n">GraphRulesCharacterUnifier</span><span class="p">(</span><span class="n">min_appearances</span><span class="o">=</span><span class="mi">10</span><span class="p">),</span>
+        <span class="n">NaiveCharactersExtractor</span><span class="p">(</span><span class="n">min_appearance</span><span class="o">=</span><span class="mi">10</span><span class="p">),</span>
         <span class="n">CoOccurrencesGraphExtractor</span><span class="p">(</span><span class="n">co_occurrences_dist</span><span class="o">=</span><span class="mi">25</span><span class="p">)</span>
     <span class="p">]</span>
 <span class="p">)</span>
@@ -149,12 +149,6 @@ <h1>The Pipeline<a class="headerlink" href="#the-pipeline" title="Permalink to t
 <span class="n">out</span> <span class="o">=</span> <span class="n">pipeline</span><span class="p">(</span><span class="n">text</span><span class="p">,</span> <span class="n">tokens</span><span class="o">=</span><span class="n">my_tokenization_function</span><span class="p">(</span><span class="n">text</span><span class="p">))</span>
 </pre></div>
 </div>
-<p>In that case, the <code class="docutils literal notranslate"><span class="pre">tokens</span></code> requirements is fulfilled at run time. If
-you don’t pass the parameter, Renard will throw the following
-exception:</p>
-<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="ne">ValueError</span><span class="p">:</span> <span class="p">[</span><span class="s2">&quot;step 1 (NLTKNamedEntityRecognizer) has unsatisfied needs (needs : {&#39;tokens&#39;}, available : {&#39;text&#39;})&quot;</span><span class="p">]</span>
-</pre></div>
-</div>
 <p>For simplicity, one can use one of the preconfigured pipelines:</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">renard.pipeline.preconfigured</span> <span class="kn">import</span> <span class="n">bert_pipeline</span>
 

py-modindex.html

@@ -96,11 +96,6 @@ <h1>Python Module Index</h1>
        <td>&#160;&#160;&#160;
        <a href="reference.html#module-renard.graph_utils"><code class="xref">renard.graph_utils</code></a></td><td>
        <em></em></td></tr>
-     <tr class="cg-1">
-       <td></td>
-       <td>&#160;&#160;&#160;
-       <a href="reference.html#module-renard.ner_utils"><code class="xref">renard.ner_utils</code></a></td><td>
-       <em></em></td></tr>
      <tr class="cg-1">
        <td></td>
        <td>&#160;&#160;&#160;