title: Custom sentence segmentation using Spacy
body: <p>I am new to Spacy and NLP. I'm facing the below issue while doing sentence segmentation using Spacy.</p>
  <p>The text I am trying to tokenise into sentences contains numbered lists (with space between numbering and actual text), like below.</p>
  <pre class="lang-py prettyprint-override"><code>import spacy
  nlp = spacy.load('en_core_web_sm')
  text = &quot;This is first sentence.\nNext is numbered list.\n1. Hello World!\n2. Hello World2!\n3. Hello World!&quot;
  text_sentences = nlp(text)
  for sentence in text_sentences.sents:
      print(sentence.text)
  </code></pre>
  <p>Output (1.,2.,3. are considered as separate lines) is:</p>
  <pre class="lang-sh prettyprint-override"><code>This is first sentence.
    
  Next is numbered list.
      
  1.
  Hello World!
   
  2.
  Hello World2!
    
  3.
  Hello World!
  </code></pre>
  <p>But if there is no space between numbering and actual text, then sentence tokenisation is fine. Like below:</p>
  <pre class="lang-py prettyprint-override"><code>import spacy
  nlp = spacy.load('en_core_web_sm')
  text = &quot;This is first sentence.\nNext is numbered list.\n1.Hello World!\n2.Hello World2!\n3.Hello World!&quot;
  text_sentences = nlp(text)
  for sentence in text_sentences.sents:
      print(sentence.text)
  </code></pre>
  <p>Output(desired) is:</p>
  <pre class="lang-sh prettyprint-override"><code>This is first sentence.
      
  Next is numbered list.
     
  1.Hello World!
      
  2.Hello World2!
      
  3.Hello World!
  </code></pre>
  <p>Please suggest whether we can customise sentence detector to do this.</p>