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re-structure repo
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‎Dockerfile

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FROM nvidia/cuda:10.0-base
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ARG http_proxy
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ENV http_proxy=$http_proxy
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ENV https_proxy=$http_proxy
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RUN apt-get update && \
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apt-get -y install build-essential && \
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apt-get -y install python3-pip && \
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apt-get clean && rm -rf /var/lib/apt/lists/*
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COPY requirements.txt /tmp
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RUN pip3 --no-cache-dir install -r /tmp/requirements.txt
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COPY . /usr/src/qurator-mono-repo
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RUN pip3 --no-cache-dir install -e /usr/src/qurator-mono-repo
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WORKDIR /usr/src/qurator-mono-repo
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CMD export LANG=C.UTF-8; env FLASK_APP=qurator/qurator_sbb_ner/webapp/app.py env FLASK_ENV=development env USE_CUDA=True flask run --host=0.0.0.0

‎Dockerfile.cpu

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FROM python:3.6-slim-stretch
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ARG http_proxy
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ENV http_proxy=$http_proxy
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ENV https_proxy=$http_proxy
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RUN apt-get update && \
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apt-get -y install build-essential && \
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apt-get clean && rm -rf /var/lib/apt/lists/*
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COPY requirements.txt /tmp
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RUN pip3 --no-cache-dir install -r /tmp/requirements.txt
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COPY . /usr/src/qurator-mono-repo
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RUN pip3 --no-cache-dir install -e /usr/src/qurator-mono-repo
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WORKDIR /usr/src/qurator-mono-repo
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CMD env FLASK_APP=qurator/qurator_sbb_ner/webapp/app.py env FLASK_ENV=development env USE_CUDA=False flask run --host=0.0.0.0

‎LICENSE

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Apache License
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Version 2.0, January 2004
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‎README.md

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***
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# Preprocessing of NER ground-truth:
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## compile_conll
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Read CONLL 2003 ner ground truth files from directory and
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write the outcome of the data parsing to some pandas DataFrame that is
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stored as pickle.
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### Usage
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```
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compile_conll --help
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```
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## compile_germ_eval
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Read germ eval .tsv files from directory and write the
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outcome of the data parsing to some pandas DataFrame that is stored as
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pickle.
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### Usage
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```
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compile_germ_eval --help
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```
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## compile_europeana_historic
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Read europeana historic ner ground truth .bio files from directory
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and write the outcome of the data parsing to some pandas
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DataFrame that is stored as pickle.
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### Usage
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```
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compile_europeana_historic --help
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```
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## compile_wikiner
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Read wikiner files from directory and write the outcome
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of the data parsing to some pandas DataFrame that is stored as pickle.
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### Usage
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```
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compile_wikiner --help
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```
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***
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# Train BERT - NER model:
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## bert-ner
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Perform BERT for NER supervised training and test/cross-validation.
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### Usage
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```
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bert-ner --help
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```

‎qurator/__init__.py

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__import__('pkg_resources').declare_namespace(__name__)

‎qurator/sbb_ner/__init__.py

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__import__('pkg_resources').declare_namespace(__name__)

‎qurator/sbb_ner/ground_truth/__init__.py

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__import__('pkg_resources').declare_namespace(__name__)

‎qurator/sbb_ner/ground_truth/conll.py

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import pandas as pd
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import click
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import codecs
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import os
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def read_gt(files, datasets):
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sentence_number = 300000
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gt_data = list()
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for filename, dataset in zip(files, datasets):
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gt_lines = [l.strip() for l in codecs.open(filename, 'r', 'latin-1')]
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word_number = 0
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for li in gt_lines:
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if li == '':
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if word_number > 0:
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sentence_number += 1
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word_number = 0
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continue
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if li.startswith('-DOCSTART-'):
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continue
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parts = li.split()
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if len(parts) == 5:
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word, _, _, _, tag = li.split()
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else:
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word, _, _, tag = li.split()
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tag = tag.upper()
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tag = tag.replace('_', '-')
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tag = tag.replace('.', '-')
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if tag not in {'B-LOC', 'B-PER', 'I-PER', 'I-ORG', 'B-ORG', 'I-LOC'}:
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tag = 'O'
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gt_data.append((sentence_number, word_number, word, tag, dataset))
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word_number += 1
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return pd.DataFrame(gt_data, columns=['nsentence', 'nword', 'word', 'tag', 'dataset'])
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@click.command()
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@click.argument('path-to-conll', type=click.Path(exists=True), required=True, nargs=1)
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@click.argument('conll-ground-truth-file', type=click.Path(), required=True, nargs=1)
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def main(path_to_conll, conll_ground_truth_file):
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"""
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Read CONLL 2003 ner ground truth files from directory <path-to-conll> and
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write the outcome of the data parsing to some pandas DataFrame
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that is stored as pickle in file <conll-ground-truth-file>.
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"""
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os.makedirs(os.path.dirname(conll_ground_truth_file), exist_ok=True)
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gt_all = read_gt(['{}/deu.dev'.format(path_to_conll),
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'{}/deu.testa'.format(path_to_conll),
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'{}/deu.testb'.format(path_to_conll),
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'{}/deu.train'.format(path_to_conll),
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'{}/eng.testa'.format(path_to_conll),
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'{}/eng.testb'.format(path_to_conll),
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'{}/eng.train'.format(path_to_conll)],
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['DE-CONLL-DEV', 'DE-CONLL-TESTA', 'DE-CONLL-TESTB', 'DE-CONLL-TRAIN',
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'EN-CONLL-TESTA', 'EN-CONLL-TESTB', 'EN-CONLL-TRAIN'])
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gt_all.to_pickle(conll_ground_truth_file)
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if __name__ == '__main__':
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main()

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