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78 lines
2.6 KiB
Python
78 lines
2.6 KiB
Python
#!/usr/bin/env python
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# coding: utf-8
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"""This example contains several snippets of methods that can be set via custom
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Doc, Token or Span attributes in spaCy v2.0. Attribute methods act like
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they're "bound" to the object and are partially applied – i.e. the object
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they're called on is passed in as the first argument.
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* Custom pipeline components: https://spacy.io//usage/processing-pipelines#custom-components
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Compatible with: spaCy v2.0.0+
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"""
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from __future__ import unicode_literals, print_function
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import plac
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from spacy.lang.en import English
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from spacy.tokens import Doc, Span
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from spacy import displacy
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from pathlib import Path
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@plac.annotations(
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output_dir=("Output directory for saved HTML", "positional", None, Path)
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)
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def main(output_dir=None):
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nlp = English() # start off with blank English class
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Doc.set_extension("overlap", method=overlap_tokens)
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doc1 = nlp("Peach emoji is where it has always been.")
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doc2 = nlp("Peach is the superior emoji.")
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print("Text 1:", doc1.text)
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print("Text 2:", doc2.text)
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print("Overlapping tokens:", doc1._.overlap(doc2))
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Doc.set_extension("to_html", method=to_html)
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doc = nlp("This is a sentence about Apple.")
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# add entity manually for demo purposes, to make it work without a model
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doc.ents = [Span(doc, 5, 6, label=nlp.vocab.strings["ORG"])]
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print("Text:", doc.text)
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doc._.to_html(output=output_dir, style="ent")
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def to_html(doc, output="/tmp", style="dep"):
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"""Doc method extension for saving the current state as a displaCy
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visualization.
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"""
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# generate filename from first six non-punct tokens
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file_name = "-".join([w.text for w in doc[:6] if not w.is_punct]) + ".html"
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html = displacy.render(doc, style=style, page=True) # render markup
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if output is not None:
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output_path = Path(output)
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if not output_path.exists():
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output_path.mkdir()
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output_file = Path(output) / file_name
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output_file.open("w", encoding="utf-8").write(html) # save to file
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print("Saved HTML to {}".format(output_file))
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else:
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print(html)
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def overlap_tokens(doc, other_doc):
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"""Get the tokens from the original Doc that are also in the comparison Doc.
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"""
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overlap = []
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other_tokens = [token.text for token in other_doc]
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for token in doc:
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if token.text in other_tokens:
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overlap.append(token)
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return overlap
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if __name__ == "__main__":
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plac.call(main)
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# Expected output:
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# Text 1: Peach emoji is where it has always been.
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# Text 2: Peach is the superior emoji.
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# Overlapping tokens: [Peach, emoji, is, .]
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