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46 lines
1.4 KiB
Python
46 lines
1.4 KiB
Python
# coding: utf-8
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"""
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Example of loading previously parsed text using spaCy's DocBin class. The example
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performs an entity count to show that the annotations are available.
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For more details, see https://spacy.io/usage/saving-loading#docs
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Installation:
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python -m spacy download en_core_web_lg
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Usage:
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python examples/load_from_docbin.py en_core_web_lg RC_2015-03-9.spacy
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"""
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from __future__ import unicode_literals
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import spacy
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from spacy.tokens import DocBin
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from timeit import default_timer as timer
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from collections import Counter
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EXAMPLE_PARSES_PATH = "RC_2015-03-9.spacy"
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def main(model="en_core_web_lg", docbin_path=EXAMPLE_PARSES_PATH):
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nlp = spacy.load(model)
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print("Reading data from {}".format(docbin_path))
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with open(docbin_path, "rb") as file_:
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bytes_data = file_.read()
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nr_word = 0
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start_time = timer()
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entities = Counter()
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docbin = DocBin().from_bytes(bytes_data)
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for doc in docbin.get_docs(nlp.vocab):
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nr_word += len(doc)
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entities.update((e.label_, e.text) for e in doc.ents)
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end_time = timer()
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msg = "Loaded {nr_word} words in {seconds} seconds ({wps} words per second)"
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wps = nr_word / (end_time - start_time)
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print(msg.format(nr_word=nr_word, seconds=end_time - start_time, wps=wps))
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print("Most common entities:")
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for (label, entity), freq in entities.most_common(30):
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print(freq, entity, label)
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if __name__ == "__main__":
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import plac
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plac.call(main)
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