title: Correct POS tags for numbers substituted with ## in spacy
body: <p>The gigaword dataset is a huge corpus used to train abstractive summarization models. It contains summaries like these:</p>
  
  <pre><code>spain 's colonial posts #.## billion euro loss
  taiwan shares close down #.## percent
  </code></pre>
  
  <p>I want to process these summaries with <em>spacy</em> and get the correct pos tag for each token. The issue is that all numbers in the dataset were replaced with # signs which spacy does not classify as numbers (<em>NUM</em>) but as other tags.</p>
  
  <pre><code>&gt;&gt;&gt; import spacy
  &gt;&gt;&gt; from spacy.tokens import Doc
  &gt;&gt;&gt; nlp = spacy.load("en_core_web_sm")
  &gt;&gt;&gt; nlp.tokenizer = lambda raw: Doc(nlp.vocab, words=raw.split(' '))
  &gt;&gt;&gt; text = "spain 's colonial posts #.## billion euro loss"
  &gt;&gt;&gt; doc = nlp(text)
  &gt;&gt;&gt; [(token.text, token.pos_) for token in doc]
  [('spain', 'PROPN'), ("'s", 'PART'), ('colonial', 'ADJ'), ('posts', 'NOUN'), ('#.##', 'PROPN'), ('billion', 'NUM'), ('euro', 'PROPN'), ('loss', 'NOUN')]
  </code></pre>
  
  <p>Is there a way to customize the POS tagger so that it classifies all tokens that only consist of #-sign and dots as numbers?</p>
  
  <p>I know you replace the spacy POS tagger with your own or fine-tune it for your domain with additional data but I don't have tagged training data where all numbers are replaced with # and I would like to change the tagger as little as possible. I would prefer having a regular expression or fixed list of tokens that are always recognized as numbers.</p>