76 lines
2.1 KiB
Python
Executable File
76 lines
2.1 KiB
Python
Executable File
#!/usr/bin/env python3
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# coding: utf-8
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print("Loading dependencies")
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import spacy
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import nltk
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from tqdm import tqdm
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import gzip
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# Wordnet
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try:
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from nltk.stem.wordnet import WordNetLemmatizer
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except:
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nltk.download("wordnet")
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from nltk.stem.wordnet import WordNetLemmatizer
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wordnet = WordNetLemmatizer()
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# Spacy
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nlp = spacy.load("en_core_web_trf", disable=["parser", "ner"])
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print("Loading initial wordlist")
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words = []
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with open("./00-dsiquintans-nounlist.txt", "r") as infile:
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for line in infile:
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words.append(line.split(",")[0].strip())
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with gzip.open("./00-frequency-list.csv.gz", "r") as infile:
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for line in infile:
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words.append(line.decode("ascii").split(",")[0])
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# Remove header
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words = words[1:]
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print(words[0:5])
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print("Lemmatizing words")
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seen_lemmatizations = set()
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with open("./01-errored-lemmatized-words.csv", "w") as erroutfile:
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erroutfile.write("WORD,ATTEMPTED_LEMMATIZATION,LEMMATIZER\n")
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with gzip.open("./01-lemmatized-words.csv.gz", "w") as outfile:
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outfile.write("WORD,LEMMATIZED_WORD,LEMMATIZER\n".encode("ascii"))
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iter = tqdm(words)
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for word in iter:
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lemmatized_words = [
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# Wordnet
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(wordnet.lemmatize(word.lower()).upper(), "WORDNET"),
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# Spacy
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(nlp(word)[0].lemma_.upper().upper(), "SPACY"),
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]
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for lemmatized_word, lemmatizer in lemmatized_words:
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if word == lemmatized_word:
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continue
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if (word, lemmatized_word) in seen_lemmatizations:
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continue
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seen_lemmatizations.add((word, lemmatized_word))
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if lemmatized_word not in words:
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iter.write(f"{lemmatized_word} ({lemmatizer}) not in all_words")
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erroutfile.write(f"{word},{lemmatized_word},{lemmatizer}\n")
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continue
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iter.write(f"{word} => {lemmatized_word} ({lemmatizer}) added")
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outfile.write(
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f"{word},{lemmatized_word},{lemmatizer}\n".encode("ascii")
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)
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