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04_05_building_holocaust_pipeline_rules_based.html
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04_05_building_holocaust_pipeline_rules_based.html
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<!DOCTYPE html>
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<title>16. Creating Rules-Based Pipeline for Holocaust Documents — Introduction to Named Entity Recognition</title>
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INTRODUCTION TO NAMED ENTITY RECOGNITION
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Key Concepts and Terms
</span>
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1. Introduction to Named Entity Recognition
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<a class="reference internal" href="01_02_introduction_to_spacy.html">
2. Introduction to spaCy
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Rules-Based NER in spaCy 3x
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3. Using SpaCy's EntityRuler
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4. Introduction to RegEx in Python and spaCy
</a>
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5. How to Add Multi-Word Tokens to spaCy Entities
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Machine Learning NER with spaCy 3x
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6. Creating a Training Set
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<a class="reference internal" href="03_02_train_spacy_ner_model.html">
7. How to Train a Base NER ML Model
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8. Examining a spaCy Model in the Folder
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9. Introduction to Word Vectors
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10. Generating Custom Word Vectors with Gensim
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11. Loading Custom Word Vectors into a spaCy Model
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Solving a Domain-Specific Problem (Holocaust)
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12. Cultivating Good Datasets for Entities
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13. Cultivating a Corpus
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<a class="reference internal" href="04_03_the_challenges_of_holocaust_ner.html">
14. The Challenges of Holocaust NER
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15. Introduction to Custom Pipes
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16. Creating the Rules-Based Pipeline
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<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#key-concepts-in-this-notebook">
16.1. Key Concepts in this Notebook
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#introduction">
16.2. Introduction
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#creating-a-blank-spacy-model">
16.3. Creating a Blank spaCy Model
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#add-pipe-for-finding-streets">
16.4. Add Pipe for Finding Streets
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#creating-a-pipe-for-finding-ships">
16.5. Creating a Pipe for Finding Ships
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#creating-a-pipe-for-finding-ghettos">
16.6. Creating a Pipe for Finding Ghettos
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#create-pipe-for-identifying-a-person">
16.7. Create Pipe for Identifying a Person
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#create-pipe-for-identifying-spouses">
16.8. Create Pipe for Identifying Spouses
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#creating-concentration-camp-pipe">
16.9. Creating Concentration Camp Pipe
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#creating-revolutionary-groups-pipe">
16.10. Creating Revolutionary Groups Pipe
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#creating-a-places-pipe">
16.11. Creating a Places Pipe
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#creating-a-geography-pipe">
16.12. Creating a Geography Pipe
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#adding-streets">
16.13. Adding Streets
</a>
</li>
<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#seeing-the-pipes-at-work">
16.14. Seeing the Pipes at Work
</a>
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<li class="toc-h2 nav-item toc-entry">
<a class="reference internal nav-link" href="#saving-a-spacy-model">
16.15. Saving a spaCy Model
</a>
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<div class="section" id="center-creating-rules-based-pipeline-for-holocaust-documents-center">
<h1><span class="section-number">16. </span><center>Creating Rules-Based Pipeline for Holocaust Documents</center><a class="headerlink" href="#center-creating-rules-based-pipeline-for-holocaust-documents-center" title="Permalink to this headline">¶</a></h1>
<center>Dr. W.J.B. Mattingly</center>
<center>Smithsonian Data Science Lab and United States Holocaust Memorial Museum</center>
<center>January 2021</center><div class="section" id="key-concepts-in-this-notebook">
<h2><span class="section-number">16.1. </span>Key Concepts in this Notebook<a class="headerlink" href="#key-concepts-in-this-notebook" title="Permalink to this headline">¶</a></h2>
<ol class="simple">
<li><p>How to add pipes to a spaCy model<br></p></li>
<li><p>How to Consider Rules<br></p></li>
<li><p>How to Implement those Rules<br></p></li>
</ol>
</div>
<div class="section" id="introduction">
<h2><span class="section-number">16.2. </span>Introduction<a class="headerlink" href="#introduction" title="Permalink to this headline">¶</a></h2>
<p>In this notebook, we will walk through some of the heuristic pipes I developed or am developing for my Holocaust NER spaCy pipeline. The purpose of these heuristic pipes is not to catch all potential entities, but to return with a high degree of confidence only true positives. We accept that the heuristics won’t catch everything because the final item in this long pipeline is a machine learning NER model that will generalize, or make predictions, on the unseen data. By structuring many heuristics in the pipeline, we can radically reduce the chances of our ML model making a wrong prediction because the all known true positives will have already been annotated.</p>
<p>I should also note that the code in my pipes is repetitious by design. As this is a textbook, it would be difficult for the reader to consistently look at the top of the notebook to identify the variable set 20 cells earlier. For this reason, I opt to recreate the variables later in the notebook. While this is bad practice, it allows the reader to understand better what is happening at any given moment in the notebook.</p>
</div>
<div class="section" id="creating-a-blank-spacy-model">
<h2><span class="section-number">16.3. </span>Creating a Blank spaCy Model<a class="headerlink" href="#creating-a-blank-spacy-model" title="Permalink to this headline">¶</a></h2>
<p>The first thing we need to do is import all of the different components from spaCy and other libraries that we will need. I will explain these as we go forward.</p>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">spacy</span>
<span class="kn">from</span> <span class="nn">spacy.util</span> <span class="kn">import</span> <span class="n">filter_spans</span>
<span class="kn">from</span> <span class="nn">spacy.tokens</span> <span class="kn">import</span> <span class="n">Span</span>
<span class="kn">from</span> <span class="nn">spacy.language</span> <span class="kn">import</span> <span class="n">Language</span>
<span class="kn">import</span> <span class="nn">re</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
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<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>INFO:tensorflow:Enabling eager execution
INFO:tensorflow:Enabling v2 tensorshape
INFO:tensorflow:Enabling resource variables
INFO:tensorflow:Enabling tensor equality
INFO:tensorflow:Enabling control flow v2
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<p>We will be using Pandas in this notebook to run data checks in a CSV file originally produced by the <a href="https://holocaustgeographies.org/">Holocaust Geographies Collaborative</a>, headed by Anne Knowles, Tim Cole, Alberto Giordano, Paul Jaskot, and Anika Walke. We will be importing RegEx because a lot of our heuristics will rely on capturing multi-word tokens.</p>
<p>Now that we have imported everything, let’s create a blank English pipeline in spaCy. As we work through this notebook, we will add pipes to it.</p>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">nlp</span> <span class="o">=</span> <span class="n">spacy</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="s2">"en_core_web_trf"</span><span class="p">)</span>
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<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>c:\users\wma22\appdata\local\programs\python\python39\lib\site-packages\spacy\util.py:730: UserWarning: [W095] Model 'en_core_web_trf' (3.0.0) was trained with spaCy v3.0 and may not be 100% compatible with the current version (3.1.1). If you see errors or degraded performance, download a newer compatible model or retrain your custom model with the current spaCy version. For more details and available updates, run: python -m spacy validate
warnings.warn(warn_msg)
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<div class="section" id="add-pipe-for-finding-streets">
<h2><span class="section-number">16.4. </span>Add Pipe for Finding Streets<a class="headerlink" href="#add-pipe-for-finding-streets" title="Permalink to this headline">¶</a></h2>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">streets_pattern</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">"([A-Z][a-z]*(strasse|straße|straat)\b|([A-Z][a-z]* (Street|St|Boulevard|Blvd|Avenue|Ave|Road|Rd|Lane|Ln|Place|Pl)(\.)*))"</span>
<span class="nd">@Language</span><span class="o">.</span><span class="n">component</span><span class="p">(</span><span class="s2">"find_streets"</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">find_streets</span><span class="p">(</span><span class="n">doc</span><span class="p">):</span>
<span class="n">text</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span>
<span class="n">camp_ents</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">original_ents</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">doc</span><span class="o">.</span><span class="n">ents</span><span class="p">)</span>
<span class="k">for</span> <span class="n">match</span> <span class="ow">in</span> <span class="n">re</span><span class="o">.</span><span class="n">finditer</span><span class="p">(</span><span class="n">streets_pattern</span><span class="p">,</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span><span class="p">):</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span> <span class="o">=</span> <span class="n">match</span><span class="o">.</span><span class="n">span</span><span class="p">()</span>
<span class="n">span</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">char_span</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">)</span>
<span class="k">if</span> <span class="n">span</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">camp_ents</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">span</span><span class="o">.</span><span class="n">start</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">end</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span><span class="p">))</span>
<span class="k">for</span> <span class="n">ent</span> <span class="ow">in</span> <span class="n">camp_ents</span><span class="p">:</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="n">ent</span>
<span class="n">per_ent</span> <span class="o">=</span> <span class="n">Span</span><span class="p">(</span><span class="n">doc</span><span class="p">,</span> <span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">"STREET"</span><span class="p">)</span>
<span class="n">original_ents</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">per_ent</span><span class="p">)</span>
<span class="n">filtered</span> <span class="o">=</span> <span class="n">filter_spans</span><span class="p">(</span><span class="n">original_ents</span><span class="p">)</span>
<span class="n">doc</span><span class="o">.</span><span class="n">ents</span> <span class="o">=</span> <span class="n">filtered</span>
<span class="k">return</span> <span class="p">(</span><span class="n">doc</span><span class="p">)</span>
<span class="n">nlp</span><span class="o">.</span><span class="n">add_pipe</span><span class="p">(</span><span class="s2">"find_streets"</span><span class="p">,</span> <span class="n">before</span><span class="o">=</span><span class="s2">"ner"</span><span class="p">)</span>
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<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span><function __main__.find_streets(doc)>
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<div class="section" id="creating-a-pipe-for-finding-ships">
<h2><span class="section-number">16.5. </span>Creating a Pipe for Finding Ships<a class="headerlink" href="#creating-a-pipe-for-finding-ships" title="Permalink to this headline">¶</a></h2>
<p>The very first pipe I want to create is a pipe that can find ships, specifically transport ships. In order to achieve this objective, this pipe does several things at once. First, it leverages RegEx to find known patterns that are always ships, e.g. multi-word tokens that may or may not begin with “S.S.”, “SS”, or “The”, followed by a list of known ships. I have opted to not use a spaCy EntityRuler here primarily because I want to expand this pipe in the future and it allows me to find matches that are more varied. Were I to implement this in an EntityRuler pipe, I would need to have many patterns sit in its knowledge-base.</p>
<p>But finding one of these patterns isn’t enough. I want to ensure that the thing referenced is in fact a ship. Many of these terms could easily be toponyms, or entities that share the same spelling but mean different things in different contexts, e.g. the Ile de France, could easily be a GPE that refers to the area around Paris. General Hosey could easily be a PERSON. To ensure toponym disambiguation, I set up several contextual clues, e.g. the list of nautical terms. If any of these words appear in area around the hit, then the heuristics assign that token the label of SHIP. If not, it ignores it and allows later pipes or the machine learning model to annotate it.</p>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">ships_pattern</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">"((S.S. |SS |The )*(Lieutenant Colonel James Barker|General Hosey|Pan Crescent|Marilyn Marlene|Winnipeg|Ile de France|Scythia|Aquitania|Empress of Britain|General A. W. Greely|General J. H. McRae|Empress of Scotland|General T. H. Bliss|New Amsterdam|Niagara|Henry Gibbs|Serpa Pinto|Mauretania|Cabo de Hornos|Julius Caesar|Ben Hecht|Sțrumah|Strumah|General Harry Taylor|General W.P. Richardson|Marine Jumper|Simon Bolivar|Pan York|Mauretania|Orduña|Wilhelm Gustloff|Orduna|General W.H. Gordon|Rakuyō Maru|Rakuyo Maru|Mouzinho|Saturnia|St. Louis|Saint Louis|Nyassa|Simon Bolivar|Queen Elizabeth|Exodus 1947|Dunera|Cap Arcona|Ernie Pyle|Hayim Arlozorov|Patria))"</span>
<span class="nd">@Language</span><span class="o">.</span><span class="n">component</span><span class="p">(</span><span class="s2">"find_ships"</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">find_ships</span><span class="p">(</span><span class="n">doc</span><span class="p">):</span>
<span class="n">text</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span>
<span class="n">new_ents</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">original_ents</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">doc</span><span class="o">.</span><span class="n">ents</span><span class="p">)</span>
<span class="n">nautical</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"ship"</span><span class="p">,</span> <span class="s2">"boat"</span><span class="p">,</span> <span class="s2">"sail"</span><span class="p">,</span> <span class="s2">"captain"</span><span class="p">,</span> <span class="s2">"sea"</span><span class="p">,</span> <span class="s2">"harbor"</span><span class="p">,</span> <span class="s2">"aboard"</span><span class="p">,</span> <span class="s2">"admiral"</span><span class="p">,</span> <span class="s2">"liner"</span><span class="p">]</span>
<span class="k">for</span> <span class="n">match</span> <span class="ow">in</span> <span class="n">re</span><span class="o">.</span><span class="n">finditer</span><span class="p">(</span><span class="n">ships_pattern</span><span class="p">,</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span><span class="p">):</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span> <span class="o">=</span> <span class="n">match</span><span class="o">.</span><span class="n">span</span><span class="p">()</span>
<span class="n">span</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">char_span</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">)</span>
<span class="n">context</span> <span class="o">=</span> <span class="n">text</span><span class="p">[</span><span class="n">start</span><span class="o">-</span><span class="mi">100</span><span class="p">:</span><span class="n">end</span><span class="o">+</span><span class="mi">100</span><span class="p">]</span>
<span class="k">if</span> <span class="nb">any</span><span class="p">(</span><span class="n">term</span> <span class="ow">in</span> <span class="n">context</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span> <span class="k">for</span> <span class="n">term</span> <span class="ow">in</span> <span class="n">nautical</span><span class="p">):</span>
<span class="k">if</span> <span class="n">span</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">new_ents</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">span</span><span class="o">.</span><span class="n">start</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">end</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">span</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">char_span</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
<span class="k">if</span> <span class="n">span</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">new_ents</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">span</span><span class="o">.</span><span class="n">start</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">end</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span><span class="p">))</span>
<span class="k">for</span> <span class="n">ent</span> <span class="ow">in</span> <span class="n">new_ents</span><span class="p">:</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="n">ent</span>
<span class="n">per_ent</span> <span class="o">=</span> <span class="n">Span</span><span class="p">(</span><span class="n">doc</span><span class="p">,</span> <span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">"SHIP"</span><span class="p">)</span>
<span class="n">original_ents</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">per_ent</span><span class="p">)</span>
<span class="n">filtered</span> <span class="o">=</span> <span class="n">filter_spans</span><span class="p">(</span><span class="n">original_ents</span><span class="p">)</span>
<span class="n">doc</span><span class="o">.</span><span class="n">ents</span> <span class="o">=</span> <span class="n">filtered</span>
<span class="k">return</span> <span class="p">(</span><span class="n">doc</span><span class="p">)</span>
<span class="n">nlp</span><span class="o">.</span><span class="n">add_pipe</span><span class="p">(</span><span class="s2">"find_ships"</span><span class="p">,</span> <span class="n">before</span><span class="o">=</span><span class="s2">"ner"</span><span class="p">)</span>
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<p>Let’s take a look and load in some data to see how this pipe functions. Remember, our goal is not to capture all ships, just ensure the ones we captured are true positives.</p>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># import glob</span>
<span class="c1"># hits = []</span>
<span class="c1"># files = glob.glob("data/new_ocr/*trs_en.txt")</span>
<span class="c1"># all_data = {}</span>
<span class="c1"># for file in files[:30]:</span>
<span class="c1"># all_hits = []</span>
<span class="c1"># with open (file, "r", encoding="utf-8") as f:</span>
<span class="c1"># print (file)</span>
<span class="c1"># text = f.read()</span>
<span class="c1"># doc = nlp(text)</span>
<span class="c1"># for ent in doc.ents:</span>
<span class="c1"># if ent.label_ == "SHIP":</span>
<span class="c1"># print (ent.text, ent.label_)</span>
<span class="c1"># print (text[ent.start_char-100:ent.end_char+100])</span>
<span class="c1"># print ()</span>
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<p>Success! File, data/new_ocr\RG-50.030.0006_trs_en.txt, referenced two ships, the Cap Arcona and the St. Louis. Now that we know we can capture ships in this manner, let’s try out the same principle on ghettos.</p>
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<div class="section" id="creating-a-pipe-for-finding-ghettos">
<h2><span class="section-number">16.6. </span>Creating a Pipe for Finding Ghettos<a class="headerlink" href="#creating-a-pipe-for-finding-ghettos" title="Permalink to this headline">¶</a></h2>
<p>As of the time of pushing this notebook, August 13, 2021, I have yet to receive a comprehensive dataset of ghettos. In the near future, this pipe will be vastly improved, similar to the concentration camp pipe below. For now, this pipe functions precisely the same way our earlier ship pipe function. Here, we’re looking for the use of the word ghetto around one of these known cities that had ghettos. This is absolutely necessary because any of these cities could be a GPE in general. The use of the word ghetto within a small contextual window is a good heuristic for assigning this city the label of GHETTO over GPE.</p>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">ghetto_pattern</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">"(Anykščiai|Anyksciai|Arad|Ashmiany|Babruĭsk|Babruisk|Balassagyarmat|Baranavichy|Barysaŭ|Barysau|Będzin|Bedzin|Bełżyce|Belzyce|Berdychiv|Berehove|Berestechko|Berezdiv|Berezhany|Berezne|Bershad'|Biała Podlaska|Biala Podlaska|Birkenau|Biała Rawska|Białystok|Bialystok|Biaroza|Bibrka|Bielsko-Biała|Biržai|Bitola|Blazhiv|Bobowa|Bochnia|Bolekhiv|Borshchuv|Boryslav|Boskovice|Brańsk|Bratslav|Brody|Brzesko|Buczacz|Budapest|Bus'k|Bychawa|Chashniki|Chrzanów|Chrzanow|Ciechanów|Ciechanow|Cieszanów|Cristuru Secuiesc|Czernowitz|Częstochowa|Czortków|Dąbrowa Górnicza|Dąbrowa Tarnowska|Damashėvichy|Daugavpils|Dokshytsy|Dombóvár|Dombrowa|Drohobycz|Drzewica|Dubrovytsia|Dzialoszyce|Dziarechyn|Dziatlava|Glebokie|Gol'shany|Góra Kalwaria|Gorodnaia|Gostynin|Gyöngyös|Hajdúszoboszló|Halushchyntsi|Halych|Hantsavichy|Haradnaia|Hatvan|Hlusk|Hlyniany|Homel'|Horodenka|Horokhiv|Hradzianka|Hrodna|Hvizdets'|Iaktoriv|Izbica Lubelska|Józefów|Kalisz|Kałuszyn|Kam'iane Pole|Kamin'-Kashyrs'kyĭ|Katowice|Kecskemét|Kelme|Kharkiv|Khmel'nyts'ka oblast'|Khmel'nyts'kyĭ|Khust|Kielce|Kisvárda|Kletsk|Kobryn|Kolbuszowa|Kolozsvár|Komarów-Osada|Kopychyntsi|Korets'|Košice|Kőszeg|Kovel'|Kozienice|Kraków|Kraśnik|Kretinga|Krośniewice|Krymne|Kryzhopil'|Kul'chyny|Kunhegyes|Kutno|Kysylyn|Ladyzhyn|Lakhva|Lask|Lęczyca|Lesko|Lida|Liepāja|Lipinki|Lithakia|Litin|Litzmannstadt|Liubavichi|Łomża|Lubaczów|Lubartów|Lublin|Łuck|Lwów|Lyubcha|Mahiliou|Maków Mazowiecki|Marcinkonys|Matejovce nad Hornádom|Mátészalka|Miechów|Międzyrzec Podlaski|Minsk|Mir|Miskolc|Modliborzyce|Mogilev|Monastyrok|Monor|Munkács|Nadvirna|Nagyvárad|Navahrudak|Novomyrhorod|Nowy Sącz|Nyíregyháza|Odessa|Oleyëvo-Korolëvka|Opatów|Opoczno|Opole|Opole Lubelskie|Orla|Orsha|Ostroh|Ostrowiec Świętokrzyski|Otwock|Ozarintsy|Ozorków|Pabianice|Papul|Parichi|Pechera|Pinsk|Piotrków Trybunalski|Płaszów|Płock|Plońsk|Praszka|Prienai|Prużana|Pruzhany|Przemyśl|Pułtusk|Radom|Radomyśl Wielki|Radun'|Rava-Rus'ka|Rawa Mazowiecka|Reghin|Ribnița|Riga|Rohatyn|Romanove Selo|Rozhyshche|Rudky|Rudnik nad Sanem|Rzeszów|Saharna|Šahy|Salgótarján|Sarny|Sátoraljaújhely|Schwientochlowitz|Senkevychivka|Sernyky|Sharhorod|Shchyrets'|Shepetivka|Shpola|Shumilino|Šiauliai|Siedlce|Siedliszcze|Sieradz|Sighetu Marmației|Skalat|Slobodka|Slonim|Slutsk|Smolensk|Sokołów Podlaski|Sokyrnytsia|Solotvyno|Soroca|Sosnowiec|Stalovichy|Stanislav|Stara Mohylʹnytsia|Starachowice|Starokostiantyniv|Stary Sącz|Stepan'|Stoczek Lukowski|Stolbëisy|Stolin|Sucha|Suchowola|Surazh|Švenčionys|Szarvas|Szczebrzeszyn|Szeged|Szolnok|Tarnogród|Tarnów|Telšiai|Terebovlia|Ternopol|Theresienstadt|Thessalonike|Timkovichi|Tlumach|Tolna|Tomaszów Mazowiecki|Torchyn|Trakai|Trebíč|Trnava|Tul'chyn|Tuliszków|Tyvriv|Uzda|Uzhhorod|Vác|Valozhyn|Velizh|Velykyĭ Bereznyĭ|Vilna|Vinnytsia|Vlonia|Volodymyr-Volyns'kyi|Vysokovskiy Rayon|Warka|Warsaw|Wisznice|Wrocław|Žagarė|Zamość|Zarichne|Zboriv|Zduńska Wola|Zhmerinka|Zhytomyr|Žiežmariai|Anyksciai|Arad|Ashmiany|Babruisk|Balassagyarmat|Baranavichy|Barysau|Bedzin|Bełzyce|Berdychiv|Berehove|Berestechko|Berezdiv|Berezhany|Berezne|Bershad'|Biała Podlaska|Biała Rawska|Białystok|Biaroza|Bibrka|Bielsko-Biała|Birzai|Bitola|Blazhiv|Bobowa|Bochnia|Bolekhiv|Borshchuv|Boryslav|Boskovice|Bransk|Bratslav|Brody|Brzesko|Buczacz|Budapest|Bus'k|Bychawa|Chashniki|Chrzanow|Ciechanow|Cieszanow|Cristuru Secuiesc|Czernowitz|Czestochowa|Czortkow|Dabrowa Gornicza|Dabrowa Tarnowska|Damashevichy|Daugavpils|Dokshytsy|Dombovar|Dombrowa|Drohobycz|Drzewica|Dubrovytsia|Dzialoszyce|Dziarechyn|Dziatlava|Glebokie|Gol'shany|Gora Kalwaria|Gorodnaia|Gostynin|Gyongyos|Hajduszoboszlo|Halushchyntsi|Halych|Hantsavichy|Haradnaia|Hatvan|Hlusk|Hlyniany|Homel'|Horodenka|Horokhiv|Hradzianka|Hrodna|Hvizdets'|Iaktoriv|Izbica Lubelska|Jozefow|Kalisz|Kałuszyn|Kam'iane Pole|Kamin'-Kashyrs'kyi|Katowice|Kecskemet|Kelme|Kharkiv|Khmel'nyts'ka oblast'|Khmel'nyts'kyi|Khust|Kielce|Kisvarda|Kletsk|Kobryn|Kolbuszowa|Kolozsvar|Komarow-Osada|Kopychyntsi|Korets'|Kosice|Koszeg|Kovel'|Kozienice|Krakow|Krasnik|Kretinga|Krosniewice|Krymne|Kryzhopil'|Kul'chyny|Kunhegyes|Kutno|Kysylyn|Ladyzhyn|Lakhva|Lask|Leczyca|Lesko|Lida|Liepaja|Lipinki|Lithakia|Litin|Litzmannstadt|Liubavichi|Łomza|Lubaczow|Lubartow|Lublin|Łuck|Lwow|Lyubcha|Mahiliou|Makow Mazowiecki|Marcinkonys|Matejovce nad Hornadom|Mateszalka|Miechow|Miedzyrzec Podlaski|Minsk|Mir|Miskolc|Modliborzyce|Mogilev|Monastyrok|Monor|Munkacs|Nadvirna|Nagyvarad|Navahrudak|Novomyrhorod|Nowy Sacz|Nyiregyhaza|Odessa|Oleyevo-Korolevka|Opatow|Opoczno|Opole|Opole Lubelskie|Orla|Orsha|Ostroh|Ostrowiec Swietokrzyski|Otwock|Ozarintsy|Ozorkow|Pabianice|Papul|Parichi|Pechera|Pinsk|Piotrkow Trybunalski|Płaszow|Płock|Plonsk|Praszka|Prienai|Pruzana|Pruzhany|Przemysl|Pułtusk|Radom|Radomysl Wielki|Radun'|Rava-Rus'ka|Rawa Mazowiecka|Reghin|Ribnita|Riga|Rohatyn|Romanove Selo|Rozhyshche|Rudky|Rudnik nad Sanem|Rzeszow|Saharna|Sahy|Salgotarjan|Sarny|Satoraljaujhely|Senkevychivka|Sernyky|Sharhorod|Shchyrets'|Shepetivka|Shpola|Shumilino|Siauliai|Siedlce|Siedliszcze|Sieradz|Sighetu Marmatiei|Skalat|Slobodka|Slonim|Slutsk|Smolensk|Sokołow Podlaski|Sokyrnytsia|Solotvyno|Soroca|Sosnowiec|Stalovichy|Stanislav|Stara Mohylʹnytsia|Starachowice|Starokostiantyniv|Stary Sacz|Stepan'|Stoczek Lukowski|Stolbeisy|Stolin|Sucha|Suchowola|Surazh|Svencionys|Szarvas|Szczebrzeszyn|Szeged|Szolnok|Tarnogrod|Tarnow|Telsiai|Terebovlia|Ternopol|Theresienstadt|Thessalonike|Timkovichi|Tlumach|Tolna|Tomaszow Mazowiecki|Torchyn|Trakai|Trebic|Trnava|Tul'chyn|Tuliszkow|Tyvriv|Uzda|Uzhhorod|Vac|Valozhyn|Velizh|Velykyi Bereznyi|Vilna|Vinnytsia|Vlonia|Volodymyr-Volyns'kyi|Vysokovskiy Rayon|Warka|Warsaw|Wisznice|Wrocław|Zagare|Zamosc|Zarichne|Zboriv|Zdunska Wola|Zhmerinka|Zhytomyr|Ziezmariai)"</span>
<span class="nd">@Language</span><span class="o">.</span><span class="n">component</span><span class="p">(</span><span class="s2">"find_ghettos"</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">find_ghettos</span><span class="p">(</span><span class="n">doc</span><span class="p">):</span>
<span class="n">text</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span>
<span class="n">ghetto_ents</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">gpe_ents</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">original_ents</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">doc</span><span class="o">.</span><span class="n">ents</span><span class="p">)</span>
<span class="k">for</span> <span class="n">match</span> <span class="ow">in</span> <span class="n">re</span><span class="o">.</span><span class="n">finditer</span><span class="p">(</span><span class="n">ghetto_pattern</span><span class="p">,</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span><span class="p">):</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span> <span class="o">=</span> <span class="n">match</span><span class="o">.</span><span class="n">span</span><span class="p">()</span>
<span class="n">span</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">char_span</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">)</span>
<span class="n">context</span> <span class="o">=</span> <span class="n">text</span><span class="p">[</span><span class="n">start</span><span class="o">-</span><span class="mi">25</span><span class="p">:</span><span class="n">end</span><span class="o">+</span><span class="mi">25</span><span class="p">]</span>
<span class="k">if</span> <span class="s2">"ghetto"</span> <span class="ow">in</span> <span class="n">context</span><span class="o">.</span><span class="n">lower</span><span class="p">():</span>
<span class="k">if</span> <span class="n">span</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">ghetto_ents</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">span</span><span class="o">.</span><span class="n">start</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">end</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="n">span</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">gpe_ents</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">span</span><span class="o">.</span><span class="n">start</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">end</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span><span class="p">))</span>
<span class="k">for</span> <span class="n">ent</span> <span class="ow">in</span> <span class="n">ghetto_ents</span><span class="p">:</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="n">ent</span>
<span class="n">per_ent</span> <span class="o">=</span> <span class="n">Span</span><span class="p">(</span><span class="n">doc</span><span class="p">,</span> <span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">"GHETTO"</span><span class="p">)</span>
<span class="n">original_ents</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">per_ent</span><span class="p">)</span>
<span class="k">for</span> <span class="n">ent</span> <span class="ow">in</span> <span class="n">gpe_ents</span><span class="p">:</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="n">ent</span>
<span class="n">per_ent</span> <span class="o">=</span> <span class="n">Span</span><span class="p">(</span><span class="n">doc</span><span class="p">,</span> <span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">"GPE"</span><span class="p">)</span>
<span class="n">original_ents</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">per_ent</span><span class="p">)</span>
<span class="n">filtered</span> <span class="o">=</span> <span class="n">filter_spans</span><span class="p">(</span><span class="n">original_ents</span><span class="p">)</span>
<span class="n">doc</span><span class="o">.</span><span class="n">ents</span> <span class="o">=</span> <span class="n">filtered</span>
<span class="k">return</span> <span class="p">(</span><span class="n">doc</span><span class="p">)</span>
<span class="n">nlp</span><span class="o">.</span><span class="n">add_pipe</span><span class="p">(</span><span class="s2">"find_ghettos"</span><span class="p">,</span> <span class="n">before</span><span class="o">=</span><span class="s2">"ner"</span><span class="p">)</span>
</pre></div>
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<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span><function __main__.find_ghettos(doc)>
</pre></div>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">second_ghettos_pattern</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">"[A-Z]\w+((-| )*[A-Z]\w+)* (g|G)hetto"</span>
<span class="nd">@Language</span><span class="o">.</span><span class="n">component</span><span class="p">(</span><span class="s2">"find_ghettos2"</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">find_ghettos2</span><span class="p">(</span><span class="n">doc</span><span class="p">):</span>
<span class="n">fps</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"That"</span><span class="p">,</span> <span class="s2">"The"</span><span class="p">]</span>
<span class="n">text</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span>
<span class="n">camp_ents</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">original_ents</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">doc</span><span class="o">.</span><span class="n">ents</span><span class="p">)</span>
<span class="k">for</span> <span class="n">match</span> <span class="ow">in</span> <span class="n">re</span><span class="o">.</span><span class="n">finditer</span><span class="p">(</span><span class="n">second_ghettos_pattern</span><span class="p">,</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span><span class="p">):</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span> <span class="o">=</span> <span class="n">match</span><span class="o">.</span><span class="n">span</span><span class="p">()</span>
<span class="n">span</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">char_span</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="o">-</span><span class="mi">7</span><span class="p">)</span>
<span class="k">if</span> <span class="n">span</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">fps</span><span class="p">:</span>
<span class="k">if</span> <span class="s2">"The "</span> <span class="ow">in</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span><span class="p">:</span>
<span class="n">camp_ents</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">span</span><span class="o">.</span><span class="n">start</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">end</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">camp_ents</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">span</span><span class="o">.</span><span class="n">start</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">end</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span><span class="p">))</span>
<span class="k">for</span> <span class="n">ent</span> <span class="ow">in</span> <span class="n">camp_ents</span><span class="p">:</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="n">ent</span>
<span class="n">per_ent</span> <span class="o">=</span> <span class="n">Span</span><span class="p">(</span><span class="n">doc</span><span class="p">,</span> <span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">"GHETTO"</span><span class="p">)</span>
<span class="n">original_ents</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">per_ent</span><span class="p">)</span>
<span class="n">filtered</span> <span class="o">=</span> <span class="n">filter_spans</span><span class="p">(</span><span class="n">original_ents</span><span class="p">)</span>
<span class="n">doc</span><span class="o">.</span><span class="n">ents</span> <span class="o">=</span> <span class="n">filtered</span>
<span class="k">return</span> <span class="p">(</span><span class="n">doc</span><span class="p">)</span>
<span class="n">nlp</span><span class="o">.</span><span class="n">add_pipe</span><span class="p">(</span><span class="s2">"find_ghettos2"</span><span class="p">,</span> <span class="n">before</span><span class="o">=</span><span class="s2">"ner"</span><span class="p">)</span>
</pre></div>
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<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span><function __main__.find_ghettos2(doc)>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># import glob</span>
<span class="c1"># hits = []</span>
<span class="c1"># files = glob.glob("data/new_ocr/*trs_en.txt")</span>
<span class="c1"># all_data = {}</span>
<span class="c1"># for file in files[:5]:</span>
<span class="c1"># all_hits = []</span>
<span class="c1"># with open (file, "r", encoding="utf-8") as f:</span>
<span class="c1"># print (file)</span>
<span class="c1"># text = f.read()</span>
<span class="c1"># doc = nlp(text)</span>
<span class="c1"># for ent in doc.ents:</span>
<span class="c1"># if ent.label_ == "GHETTO":</span>
<span class="c1"># print (ent.text, ent.label_)</span>
<span class="c1"># print (text[ent.start_char-100:ent.end_char+100])</span>
<span class="c1"># print ()</span>
</pre></div>
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<p>As we can see, the pipe is working. We’ve grabbed three instances of Warsaw in data/new_ocr\RG-50.030.0001_trs_en.txt.</p>
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<div class="section" id="create-pipe-for-identifying-a-person">
<h2><span class="section-number">16.7. </span>Create Pipe for Identifying a Person<a class="headerlink" href="#create-pipe-for-identifying-a-person" title="Permalink to this headline">¶</a></h2>
<p>For PERSON, we will be leveraging spaCy’s small model, but we can add some heuristics that will greatly improve the results. The heuristics here is any known salutation capitalized followed by a series of proper nouns. This RegEx “(?:[A-Z]\w+[ -]?)+)” allows us to grab all continuous capital words and then break when it encounters a non capital letter followed by a space. In English, these will always be PERSON entities.</p>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">people_pattern</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">"((((Mr|Mrs|Miss|Dr|Col|Adm|Lt|Cap|Cpt|Fr|Cl|Cln|Sgt)\.)|(Frau|Herr|President|Rabbi|Queen|Prince|Princess|Pope|Father|Bishop|King|Cardinal|General|Liutenant|Colonel|Lieutenant Colonel|Private|Admiral|Captain|Sergeant|Sergeant First Class|Staff Sergeant|Sergeant Major|Corp Sergeant Major|Field Sergeant|Technical Sergeant|Corporal|Lance Corporal|Ensign|2nd Lieutenant|1st Lieutenant|Major|Hauptmann|Staff Captain|Oberst|Oberstlieutenant)) (?:[A-Z]\w+[ -]?)+)(the [A-Z]\w*|I\w*|X\w*|v\w*)*"</span>
<span class="nd">@Language</span><span class="o">.</span><span class="n">component</span><span class="p">(</span><span class="s2">"find_people"</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">find_people</span><span class="p">(</span><span class="n">doc</span><span class="p">):</span>
<span class="n">text</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span>
<span class="n">match_ents</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">original_ents</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">doc</span><span class="o">.</span><span class="n">ents</span><span class="p">)</span>
<span class="k">for</span> <span class="n">match</span> <span class="ow">in</span> <span class="n">re</span><span class="o">.</span><span class="n">finditer</span><span class="p">(</span><span class="n">people_pattern</span><span class="p">,</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span><span class="p">):</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span> <span class="o">=</span> <span class="n">match</span><span class="o">.</span><span class="n">span</span><span class="p">()</span>
<span class="n">span</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">char_span</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">)</span>
<span class="k">if</span> <span class="n">span</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">match_ents</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">span</span><span class="o">.</span><span class="n">start</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">end</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">span</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">char_span</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
<span class="k">if</span> <span class="n">span</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">match_ents</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">span</span><span class="o">.</span><span class="n">start</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">end</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span><span class="p">))</span>
<span class="k">for</span> <span class="n">ent</span> <span class="ow">in</span> <span class="n">match_ents</span><span class="p">:</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="n">ent</span>
<span class="n">per_ent</span> <span class="o">=</span> <span class="n">Span</span><span class="p">(</span><span class="n">doc</span><span class="p">,</span> <span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">"PERSON"</span><span class="p">)</span>
<span class="n">original_ents</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">per_ent</span><span class="p">)</span>
<span class="n">filtered</span> <span class="o">=</span> <span class="n">filter_spans</span><span class="p">(</span><span class="n">original_ents</span><span class="p">)</span>
<span class="n">doc</span><span class="o">.</span><span class="n">ents</span> <span class="o">=</span> <span class="n">filtered</span>
<span class="k">return</span> <span class="p">(</span><span class="n">doc</span><span class="p">)</span>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">nlp</span><span class="o">.</span><span class="n">add_pipe</span><span class="p">(</span><span class="s2">"find_people"</span><span class="p">,</span> <span class="n">before</span><span class="o">=</span><span class="s2">"ner"</span><span class="p">)</span>
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<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span><function __main__.find_people(doc)>
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<div class="section" id="create-pipe-for-identifying-spouses">
<h2><span class="section-number">16.8. </span>Create Pipe for Identifying Spouses<a class="headerlink" href="#create-pipe-for-identifying-spouses" title="Permalink to this headline">¶</a></h2>
<p>Often times in historical documents the identity of people are referenced collectively. In some instances, such as those of spouses, this results in the name of the woman being attached to the name of her husband. The purpose of this SPOUSAL entity is to identify such constructs so that users can manipulate the output and reconstruct each individual singularly.</p>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">spousal_pattern</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">"((Mr|Mrs|Miss|Dr)(\.)* and (Mr|Mrs|Miss|Dr)(\.)* (?:[A-Z]\w+[ -]?)+)"</span>
<span class="nd">@Language</span><span class="o">.</span><span class="n">component</span><span class="p">(</span><span class="s2">"find_spousal"</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">find_spousal</span><span class="p">(</span><span class="n">doc</span><span class="p">):</span>
<span class="n">text</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span>
<span class="n">new_ents</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">original_ents</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">doc</span><span class="o">.</span><span class="n">ents</span><span class="p">)</span>
<span class="k">for</span> <span class="n">match</span> <span class="ow">in</span> <span class="n">re</span><span class="o">.</span><span class="n">finditer</span><span class="p">(</span><span class="n">spousal_pattern</span><span class="p">,</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span><span class="p">):</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span> <span class="o">=</span> <span class="n">match</span><span class="o">.</span><span class="n">span</span><span class="p">()</span>
<span class="n">span</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">char_span</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">)</span>
<span class="k">if</span> <span class="n">span</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">new_ents</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">span</span><span class="o">.</span><span class="n">start</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">end</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">span</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">char_span</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
<span class="k">if</span> <span class="n">span</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">new_ents</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">span</span><span class="o">.</span><span class="n">start</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">end</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span><span class="p">))</span>
<span class="k">for</span> <span class="n">ent</span> <span class="ow">in</span> <span class="n">new_ents</span><span class="p">:</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="n">ent</span>
<span class="n">per_ent</span> <span class="o">=</span> <span class="n">Span</span><span class="p">(</span><span class="n">doc</span><span class="p">,</span> <span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">"SPOUSAL"</span><span class="p">)</span>
<span class="n">original_ents</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">per_ent</span><span class="p">)</span>
<span class="n">filtered</span> <span class="o">=</span> <span class="n">filter_spans</span><span class="p">(</span><span class="n">original_ents</span><span class="p">)</span>
<span class="n">doc</span><span class="o">.</span><span class="n">ents</span> <span class="o">=</span> <span class="n">filtered</span>
<span class="k">return</span> <span class="p">(</span><span class="n">doc</span><span class="p">)</span>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">nlp</span><span class="o">.</span><span class="n">add_pipe</span><span class="p">(</span><span class="s2">"find_spousal"</span><span class="p">,</span> <span class="n">before</span><span class="o">=</span><span class="s2">"ner"</span><span class="p">)</span>
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<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span><function __main__.find_spousal(doc)>
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<div class="section" id="creating-concentration-camp-pipe">
<h2><span class="section-number">16.9. </span>Creating Concentration Camp Pipe<a class="headerlink" href="#creating-concentration-camp-pipe" title="Permalink to this headline">¶</a></h2>
<p>The correct identification of camp is one of the most important pipes in this pipeline. There are two concentration camp pipes. The first pipe looks at all known camps and subcamps and then looks for surrounding words to identify the context. The second pipe is less strict. It looks for all known main concentration camps without context. The reason for this is because sometimes the subcamps have the same names as frequently cited cities, e.g. Berlin or Neustadt. This is particularly true of the subcamps. The main camps, however, are frequently referenced to the camp itself. Both pipes are activated by default, but a user can deactivate one or other.</p>
<p>Throughout this pipe, you will see many functions that contain the name “getter”. These are custom functions that allow us to add special attributes to our entity spans. If you scroll down to the bottom of this section, you will see that we can use the HGC dataset for conentration camps to retrieve other salient information, such as the subcamp’s main camp, its longitude and latitude, opening date, closing date, etc.</p>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">subcamp_getter</span><span class="p">(</span><span class="n">hit</span><span class="p">):</span>
<span class="n">hit</span> <span class="o">=</span> <span class="n">hit</span><span class="o">.</span><span class="n">text</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">"data/hgc_data.csv"</span><span class="p">)</span>
<span class="n">subcamps</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">Main</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
<span class="n">camps</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">SubcampMattingly</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
<span class="n">i</span><span class="o">=</span><span class="mi">0</span>
<span class="n">potential</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">camps</span><span class="p">:</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">all_c</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">"^"</span><span class="p">)</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">all_c</span><span class="p">:</span>
<span class="n">c</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s2">"\("</span><span class="p">,</span> <span class="s2">"("</span><span class="p">)</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s2">"\)"</span><span class="p">,</span> <span class="s2">")"</span><span class="p">)</span>
<span class="c1"># if c == "Buna-Monowitz (Auschwitz III)":</span>
<span class="c1"># print (c)</span>
<span class="k">if</span> <span class="n">hit</span><span class="o">.</span><span class="n">strip</span><span class="p">()</span> <span class="o">==</span> <span class="n">c</span><span class="o">.</span><span class="n">strip</span><span class="p">():</span>
<span class="c1"># print (hit, c)</span>
<span class="k">if</span> <span class="n">subcamps</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">potential</span><span class="p">:</span>
<span class="n">potential</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">subcamps</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
<span class="k">except</span><span class="p">:</span>
<span class="ne">AttributeError</span>
<span class="n">i</span><span class="o">=</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span>
<span class="k">return</span> <span class="p">(</span><span class="n">potential</span><span class="p">)</span>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">date_open_getter</span><span class="p">(</span><span class="n">hit</span><span class="p">):</span>
<span class="n">hit</span> <span class="o">=</span> <span class="n">hit</span><span class="o">.</span><span class="n">text</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">"data/hgc_data.csv"</span><span class="p">)</span>
<span class="n">dates</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">Date_Open</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
<span class="n">camps</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">SubcampMattingly</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
<span class="n">i</span><span class="o">=</span><span class="mi">0</span>
<span class="n">potential</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">camps</span><span class="p">:</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">all_c</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">"^"</span><span class="p">)</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">all_c</span><span class="p">:</span>
<span class="k">if</span> <span class="n">hit</span> <span class="o">==</span> <span class="n">c</span><span class="p">:</span>
<span class="k">if</span> <span class="n">dates</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">potential</span><span class="p">:</span>
<span class="n">potential</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dates</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
<span class="k">except</span><span class="p">:</span>
<span class="ne">AttributeError</span>
<span class="n">i</span><span class="o">=</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span>
<span class="k">return</span> <span class="p">(</span><span class="n">potential</span><span class="p">)</span>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">date_closed_getter</span><span class="p">(</span><span class="n">hit</span><span class="p">):</span>
<span class="n">hit</span> <span class="o">=</span> <span class="n">hit</span><span class="o">.</span><span class="n">text</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">"data/hgc_data.csv"</span><span class="p">)</span>
<span class="n">dates</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">Date_Close</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
<span class="n">camps</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">SubcampMattingly</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
<span class="n">i</span><span class="o">=</span><span class="mi">0</span>
<span class="n">potential</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">camps</span><span class="p">:</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">all_c</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">"^"</span><span class="p">)</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">all_c</span><span class="p">:</span>
<span class="k">if</span> <span class="n">hit</span> <span class="o">==</span> <span class="n">c</span><span class="p">:</span>
<span class="k">if</span> <span class="n">dates</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">potential</span><span class="p">:</span>
<span class="n">potential</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dates</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
<span class="k">except</span><span class="p">:</span>
<span class="ne">AttributeError</span>
<span class="n">i</span><span class="o">=</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span>
<span class="k">return</span> <span class="p">(</span><span class="n">potential</span><span class="p">)</span>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">latlong_getter</span><span class="p">(</span><span class="n">hit</span><span class="p">):</span>
<span class="n">hit</span> <span class="o">=</span> <span class="n">hit</span><span class="o">.</span><span class="n">text</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">"data/hgc_data.csv"</span><span class="p">)</span>
<span class="n">lats</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">LAT</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
<span class="n">longs</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">LONG</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
<span class="n">camps</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">SubcampMattingly</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
<span class="n">i</span><span class="o">=</span><span class="mi">0</span>
<span class="n">potential</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">camps</span><span class="p">:</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">all_c</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">"^"</span><span class="p">)</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">all_c</span><span class="p">:</span>
<span class="k">if</span> <span class="n">hit</span> <span class="o">==</span> <span class="n">c</span><span class="p">:</span>
<span class="k">if</span> <span class="n">lats</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">potential</span><span class="p">:</span>
<span class="n">potential</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">lats</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">longs</span><span class="p">[</span><span class="n">i</span><span class="p">]))</span>
<span class="k">except</span><span class="p">:</span>
<span class="ne">AttributeError</span>
<span class="n">i</span><span class="o">=</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span>
<span class="k">return</span> <span class="p">(</span><span class="n">potential</span><span class="p">)</span>
</pre></div>
</div>
</div>
</div>
<div class="cell docutils container">
<div class="cell_input docutils container">
<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">hgc_id_getter</span><span class="p">(</span><span class="n">hit</span><span class="p">):</span>
<span class="n">hit</span> <span class="o">=</span> <span class="n">hit</span><span class="o">.</span><span class="n">text</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">"data/hgc_data.csv"</span><span class="p">)</span>
<span class="n">ids</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">HGC_ID</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
<span class="n">camps</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">SubcampMattingly</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
<span class="n">i</span><span class="o">=</span><span class="mi">0</span>
<span class="n">potential</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">camps</span><span class="p">:</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">all_c</span> <span class="o">=</span> <span class="n">c</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">"^"</span><span class="p">)</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">all_c</span><span class="p">:</span>
<span class="k">if</span> <span class="n">hit</span> <span class="o">==</span> <span class="n">c</span><span class="p">:</span>
<span class="k">if</span> <span class="n">ids</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">potential</span><span class="p">:</span>
<span class="n">potential</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">ids</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
<span class="k">except</span><span class="p">:</span>
<span class="ne">AttributeError</span>
<span class="n">i</span><span class="o">=</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span>
<span class="k">return</span> <span class="p">(</span><span class="n">potential</span><span class="p">)</span>
</pre></div>
</div>
</div>
</div>
<div class="cell docutils container">
<div class="cell_input docutils container">
<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">camp_type_getter</span><span class="p">(</span><span class="n">hit</span><span class="p">):</span>
<span class="n">hit</span> <span class="o">=</span> <span class="n">hit</span><span class="o">.</span><span class="n">text</span>
</pre></div>
</div>
</div>
</div>
<div class="cell docutils container">
<div class="cell_input docutils container">
<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s2">"data/hgc_data.csv"</span><span class="p">)</span>
<span class="n">camps</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">SubcampMattingly</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
<span class="n">subcamps</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">Main</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
<span class="n">i</span><span class="o">=</span><span class="mi">0</span>
<span class="n">final_camps</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">camps</span><span class="p">:</span>
<span class="k">if</span> <span class="n">c</span> <span class="o">!=</span> <span class="s2">"nan"</span> <span class="ow">and</span> <span class="n">c</span> <span class="o">!=</span> <span class="s2">"FALSE"</span><span class="p">:</span>
<span class="k">if</span> <span class="n">subcamps</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">!=</span> <span class="s2">"nan"</span> <span class="ow">and</span> <span class="n">subcamps</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">!=</span> <span class="s2">"FALSE"</span><span class="p">:</span>
<span class="k">try</span><span class="p">:</span>
<span class="k">if</span> <span class="n">c</span><span class="o">.</span><span class="n">split</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span> <span class="o">!=</span> <span class="s2">""</span><span class="p">:</span>
<span class="n">c</span><span class="o">=</span><span class="n">c</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s2">"*"</span><span class="p">,</span> <span class="s2">""</span><span class="p">)</span>
<span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">c</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">"^"</span><span class="p">):</span>
<span class="n">final_camps</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">item</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s2">"("</span><span class="p">,</span> <span class="s2">"\("</span><span class="p">)</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s2">")"</span><span class="p">,</span> <span class="s2">"\)"</span><span class="p">)</span><span class="o">.</span><span class="n">strip</span><span class="p">())</span>
<span class="k">except</span><span class="p">:</span>
<span class="ne">AttributeError</span>
<span class="n">i</span><span class="o">=</span><span class="n">i</span><span class="o">+</span><span class="mi">1</span>
<span class="n">final_camps</span><span class="o">.</span><span class="n">sort</span><span class="p">(</span><span class="n">key</span><span class="o">=</span><span class="nb">len</span><span class="p">,</span> <span class="n">reverse</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">final_list</span> <span class="o">=</span> <span class="s2">"|"</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">final_camps</span><span class="p">)</span>
<span class="n">strict_camps_pattern</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">"("</span><span class="o">+</span><span class="n">final_list</span><span class="o">+</span><span class="s2">")"</span>
<span class="c1"># print (strict_camps_pattern)</span>
<span class="nd">@Language</span><span class="o">.</span><span class="n">component</span><span class="p">(</span><span class="s2">"find_camps_strict"</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">find_camps_strict</span><span class="p">(</span><span class="n">doc</span><span class="p">):</span>
<span class="n">text</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span>
<span class="n">camp_ents</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">original_ents</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">doc</span><span class="o">.</span><span class="n">ents</span><span class="p">)</span>
<span class="n">context_terms</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"camp"</span><span class="p">,</span> <span class="s2">"concentration"</span><span class="p">,</span> <span class="s2">"labor"</span><span class="p">,</span> <span class="s2">"forced"</span><span class="p">,</span> <span class="s2">"gas"</span><span class="p">,</span> <span class="s2">"chamber"</span><span class="p">]</span>
<span class="k">for</span> <span class="n">match</span> <span class="ow">in</span> <span class="n">re</span><span class="o">.</span><span class="n">finditer</span><span class="p">(</span><span class="n">strict_camps_pattern</span><span class="p">,</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span><span class="p">):</span>
<span class="c1"># print (match)</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span> <span class="o">=</span> <span class="n">match</span><span class="o">.</span><span class="n">span</span><span class="p">()</span>
<span class="n">span</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">char_span</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">)</span>
<span class="n">context</span> <span class="o">=</span> <span class="n">text</span><span class="p">[</span><span class="n">start</span><span class="o">-</span><span class="mi">100</span><span class="p">:</span><span class="n">end</span><span class="o">+</span><span class="mi">100</span><span class="p">]</span>
<span class="k">if</span> <span class="nb">any</span><span class="p">(</span><span class="n">term</span> <span class="ow">in</span> <span class="n">context</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span> <span class="k">for</span> <span class="n">term</span> <span class="ow">in</span> <span class="n">context_terms</span><span class="p">):</span>
<span class="k">if</span> <span class="n">span</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="c1"># print (span)</span>
<span class="n">camp_ents</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">span</span><span class="o">.</span><span class="n">start</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">end</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span><span class="p">))</span>
<span class="k">for</span> <span class="n">ent</span> <span class="ow">in</span> <span class="n">camp_ents</span><span class="p">:</span>
<span class="c1"># print (ent)</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="n">ent</span>
<span class="n">per_ent</span> <span class="o">=</span> <span class="n">Span</span><span class="p">(</span><span class="n">doc</span><span class="p">,</span> <span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">"CAMP"</span><span class="p">)</span>
<span class="n">per_ent</span><span class="o">.</span><span class="n">set_extension</span><span class="p">(</span><span class="s2">"subcamp"</span><span class="p">,</span> <span class="n">getter</span><span class="o">=</span><span class="n">subcamp_getter</span><span class="p">,</span> <span class="n">force</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">per_ent</span><span class="o">.</span><span class="n">set_extension</span><span class="p">(</span><span class="s2">"date_open"</span><span class="p">,</span> <span class="n">getter</span><span class="o">=</span><span class="n">date_open_getter</span><span class="p">,</span> <span class="n">force</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">per_ent</span><span class="o">.</span><span class="n">set_extension</span><span class="p">(</span><span class="s2">"date_closed"</span><span class="p">,</span> <span class="n">getter</span><span class="o">=</span><span class="n">date_closed_getter</span><span class="p">,</span> <span class="n">force</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">per_ent</span><span class="o">.</span><span class="n">set_extension</span><span class="p">(</span><span class="s2">"latlong"</span><span class="p">,</span> <span class="n">getter</span><span class="o">=</span><span class="n">latlong_getter</span><span class="p">,</span> <span class="n">force</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">per_ent</span><span class="o">.</span><span class="n">set_extension</span><span class="p">(</span><span class="s2">"hgc_id"</span><span class="p">,</span> <span class="n">getter</span><span class="o">=</span><span class="n">hgc_id_getter</span><span class="p">,</span> <span class="n">force</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">original_ents</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">per_ent</span><span class="p">)</span>
<span class="n">filtered</span> <span class="o">=</span> <span class="n">filter_spans</span><span class="p">(</span><span class="n">original_ents</span><span class="p">)</span>
<span class="n">doc</span><span class="o">.</span><span class="n">ents</span> <span class="o">=</span> <span class="n">filtered</span>
<span class="k">return</span> <span class="p">(</span><span class="n">doc</span><span class="p">)</span>
</pre></div>
</div>
</div>
</div>
<div class="cell docutils container">
<div class="cell_input docutils container">
<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">camps_pattern</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">"(Alderney|Amersfoort|Auschwitz|Banjica|Belzec|Bergen-Belsen|Bernburg|Bogdanovka|Bolzano|Bor|Breendonk|Breitenau|Buchenwald|Chelmno|Dachau|Drancy|Falstad|Flossenburg|Fort VII|Fossoli|Grini|Gross-Rosen|Herzogenbusch|Hinzert|Janowska|Jasenovac|Kaiserwald|Kaunas|Kemna|Klooga|Le Vernet|Majdanek|Malchow|Maly Trostenets|Mechelen|Mittelbau-Dora|Natzweiler-Struthof|Neuengamme|Niederhagen|Oberer Kuhberg|Oranienburg|Osthofen|Plaszow|Ravensbruck|Risiera di San Sabba|Sachsenhausen|Sajmište|Salaspils|Sobibor|Soldau|Stutthof|Theresienstadt|Trawniki|Treblinka|Vaivara)(-[A-Z]\S+)*"</span>
<span class="nd">@Language</span><span class="o">.</span><span class="n">component</span><span class="p">(</span><span class="s2">"find_camps"</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">find_camps</span><span class="p">(</span><span class="n">doc</span><span class="p">):</span>
<span class="n">text</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span>
<span class="n">camp_ents</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">original_ents</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">doc</span><span class="o">.</span><span class="n">ents</span><span class="p">)</span>
<span class="k">for</span> <span class="n">match</span> <span class="ow">in</span> <span class="n">re</span><span class="o">.</span><span class="n">finditer</span><span class="p">(</span><span class="n">camps_pattern</span><span class="p">,</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span><span class="p">):</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span> <span class="o">=</span> <span class="n">match</span><span class="o">.</span><span class="n">span</span><span class="p">()</span>
<span class="n">span</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">char_span</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">)</span>
<span class="k">if</span> <span class="n">span</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">camp_ents</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">span</span><span class="o">.</span><span class="n">start</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">end</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span><span class="p">))</span>
<span class="k">for</span> <span class="n">ent</span> <span class="ow">in</span> <span class="n">camp_ents</span><span class="p">:</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="n">ent</span>
<span class="n">per_ent</span> <span class="o">=</span> <span class="n">Span</span><span class="p">(</span><span class="n">doc</span><span class="p">,</span> <span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">"CAMP"</span><span class="p">)</span>
<span class="n">per_ent</span><span class="o">.</span><span class="n">set_extension</span><span class="p">(</span><span class="s2">"subcamp"</span><span class="p">,</span> <span class="n">getter</span><span class="o">=</span><span class="n">subcamp_getter</span><span class="p">,</span> <span class="n">force</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">per_ent</span><span class="o">.</span><span class="n">set_extension</span><span class="p">(</span><span class="s2">"date_open"</span><span class="p">,</span> <span class="n">getter</span><span class="o">=</span><span class="n">date_open_getter</span><span class="p">,</span> <span class="n">force</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">per_ent</span><span class="o">.</span><span class="n">set_extension</span><span class="p">(</span><span class="s2">"date_closed"</span><span class="p">,</span> <span class="n">getter</span><span class="o">=</span><span class="n">date_closed_getter</span><span class="p">,</span> <span class="n">force</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">per_ent</span><span class="o">.</span><span class="n">set_extension</span><span class="p">(</span><span class="s2">"latlong"</span><span class="p">,</span> <span class="n">getter</span><span class="o">=</span><span class="n">latlong_getter</span><span class="p">,</span> <span class="n">force</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">per_ent</span><span class="o">.</span><span class="n">set_extension</span><span class="p">(</span><span class="s2">"hgc_id"</span><span class="p">,</span> <span class="n">getter</span><span class="o">=</span><span class="n">hgc_id_getter</span><span class="p">,</span> <span class="n">force</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">original_ents</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">per_ent</span><span class="p">)</span>
<span class="n">filtered</span> <span class="o">=</span> <span class="n">filter_spans</span><span class="p">(</span><span class="n">original_ents</span><span class="p">)</span>
<span class="n">doc</span><span class="o">.</span><span class="n">ents</span> <span class="o">=</span> <span class="n">filtered</span>
<span class="k">return</span> <span class="p">(</span><span class="n">doc</span><span class="p">)</span>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">second_camps_pattern</span> <span class="o">=</span> <span class="sa">r</span><span class="s2">"[A-Z]\w+((-| )*[A-Z]\w+)* (c|C)oncentration (c|C)amp"</span>
<span class="nd">@Language</span><span class="o">.</span><span class="n">component</span><span class="p">(</span><span class="s2">"find_camps2"</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">find_camps2</span><span class="p">(</span><span class="n">doc</span><span class="p">):</span>
<span class="n">text</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span>
<span class="n">camp_ents</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">original_ents</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="n">doc</span><span class="o">.</span><span class="n">ents</span><span class="p">)</span>
<span class="k">for</span> <span class="n">match</span> <span class="ow">in</span> <span class="n">re</span><span class="o">.</span><span class="n">finditer</span><span class="p">(</span><span class="n">second_camps_pattern</span><span class="p">,</span> <span class="n">doc</span><span class="o">.</span><span class="n">text</span><span class="p">):</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span> <span class="o">=</span> <span class="n">match</span><span class="o">.</span><span class="n">span</span><span class="p">()</span>
<span class="n">span</span> <span class="o">=</span> <span class="n">doc</span><span class="o">.</span><span class="n">char_span</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="o">-</span><span class="mi">19</span><span class="p">)</span>
<span class="k">if</span> <span class="n">span</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">camp_ents</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">span</span><span class="o">.</span><span class="n">start</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">end</span><span class="p">,</span> <span class="n">span</span><span class="o">.</span><span class="n">text</span><span class="p">))</span>
<span class="k">for</span> <span class="n">ent</span> <span class="ow">in</span> <span class="n">camp_ents</span><span class="p">:</span>
<span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">name</span> <span class="o">=</span> <span class="n">ent</span>
<span class="n">per_ent</span> <span class="o">=</span> <span class="n">Span</span><span class="p">(</span><span class="n">doc</span><span class="p">,</span> <span class="n">start</span><span class="p">,</span> <span class="n">end</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">"CAMP"</span><span class="p">)</span>
<span class="n">original_ents</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">per_ent</span><span class="p">)</span>
<span class="n">filtered</span> <span class="o">=</span> <span class="n">filter_spans</span><span class="p">(</span><span class="n">original_ents</span><span class="p">)</span>
<span class="n">doc</span><span class="o">.</span><span class="n">ents</span> <span class="o">=</span> <span class="n">filtered</span>
<span class="k">return</span> <span class="p">(</span><span class="n">doc</span><span class="p">)</span>
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<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">nlp</span><span class="o">.</span><span class="n">add_pipe</span><span class="p">(</span><span class="s2">"find_camps_strict"</span><span class="p">,</span> <span class="n">before</span><span class="o">=</span><span class="s2">"ner"</span><span class="p">)</span>
<span class="n">nlp</span><span class="o">.</span><span class="n">add_pipe</span><span class="p">(</span><span class="s2">"find_camps"</span><span class="p">,</span> <span class="n">before</span><span class="o">=</span><span class="s2">"ner"</span><span class="p">)</span>
<span class="n">nlp</span><span class="o">.</span><span class="n">add_pipe</span><span class="p">(</span><span class="s2">"find_camps2"</span><span class="p">,</span> <span class="n">before</span><span class="o">=</span><span class="s2">"ner"</span><span class="p">)</span>
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