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Upload dataset_extraction.py (#11)
Browse files- Upload dataset_extraction.py (3037a7c96c513edd7a68b8e32bdd57bdad5a64d4)
Co-authored-by: Linxiao Zhu <[email protected]>
- dataset_extraction.py +44 -0
dataset_extraction.py
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from typing import List, Tuple
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import torch
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import nltk
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from SciAssist import DatasetExtraction
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device = "gpu" if torch.cuda.is_available() else "cpu"
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de_pipeline = DatasetExtraction(os_name="nt")
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def de_for_str(input):
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list_input = nltk.sent_tokenize(input)
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results = de_pipeline.extract(list_input, type="str", save_results=False)
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# output = []
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# for res in results["dataset_mentions"]:
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# output.append(f"{res}\n\n")
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# return "".join(output)
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output = []
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for mention_pair in results["dataset_mentions"]:
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output.append((mention_pair[0], mention_pair[1]))
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output.append(("\n\n", None))
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return output
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def de_for_file(input):
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if input == None:
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return None
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filename = input.name
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# Identify the format of input and parse reference strings
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if filename[-4:] == ".txt":
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results = de_pipeline.extract(filename, type="txt", save_results=False)
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elif filename[-4:] == ".pdf":
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results = de_pipeline.extract(filename, type="pdf", save_results=False)
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else:
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return [("File Format Error !", None)]
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output = []
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for mention_pair in results["dataset_mentions"]:
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output.append((mention_pair[0], mention_pair[1]))
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output.append(("\n\n", None))
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return output
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de_str_example = "BAKIS incorporates information derived from the bank balance sheets and supervisory reports of all German banks ."
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