mirror of
https://gitlab.ub.uni-bielefeld.de/sfb1288inf/nlp.git
synced 2024-12-25 20:04:17 +00:00
Preliminary work
This commit is contained in:
Patrick Jentsch
parent
5139fd9727
commit
4dea95a108
11
nlp
11
nlp
@ -37,6 +37,11 @@ class NLPPipelineJob:
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self.file = file
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self.name = os.path.basename(file).rsplit('.', 1)[0]
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self.output_dir = output_dir
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catma_stand_off_data_file = file.rsplit('.', 1)[0] + '.catma-stand-off.json' # noqa
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if os.path.exists(catma_stand_off_data_file):
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self.catma_stand_off_data_file = catma_stand_off_data_file
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else:
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self.catma_stand_off_data_file = None
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class NLPPipeline(WorkflowRunner):
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@ -93,10 +98,12 @@ class NLPPipeline(WorkflowRunner):
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vrt_creation_tasks = []
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for i, job in enumerate(self.jobs):
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output_file = os.path.join(job.output_dir, '{}.vrt'.format(job.name)) # noqa
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nlp_file = os.path.join(job.output_dir, '{}.nopaque-stand-off.json'.format(job.name)) # noqa
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nopaque_stand_off_data_file = os.path.join(job.output_dir, '{}.nopaque-stand-off.json'.format(job.name)) # noqa
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cmd = 'vrt-creator'
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cmd += ' "{}"'.format(job.file)
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cmd += ' "{}"'.format(nlp_file)
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cmd += ' "{}"'.format(nopaque_stand_off_data_file)
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if job.catma_stand_off_data_file is not None:
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cmd += ' --catma-stand-off-data "{}"'.format(job.catma_stand_off_data_file) # noqa
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cmd += ' "{}"'.format(output_file)
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deps = 'nlp_-_{}'.format(i)
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lbl = 'vrt_creation_-_{}'.format(i)
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0
packages/stand-off-data-py/setup.py
Normal file
0
packages/stand-off-data-py/setup.py
Normal file
126
packages/stand-off-data-py/stand_off_data/models.py
Normal file
126
packages/stand-off-data-py/stand_off_data/models.py
Normal file
@ -0,0 +1,126 @@
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'''
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'generator': {
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'name': 'nopaque NLP service',
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'version': '1.0.0',
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'arguments': {
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'check_encoding': args.check_encoding,
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'language': args.language
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}
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},
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'file': {
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'encoding': encoding,
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'md5': text_md5.hexdigest(),
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'name': os.path.basename(args.input)
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}
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'''
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class StandOffData:
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def __init__(self, attrs):
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self.tags = {tag_definition.id: tag_definition for tag_definition in
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[TagDefinition(x) for x in attrs.get('tags', [])]}
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self.annotations = [TagAnnotation(x, self.tags) for x in
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attrs.get('annotations', [])]
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class TagAnnotation:
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def __init__(self, attrs, tag_lookup):
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self.tag_id = attrs['tag_id']
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self.tag_lookup = tag_lookup
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if self.tag_id not in self.tag_lookup:
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raise Exception('Unknown tag id: {}'.format(self.tag_id))
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self.start = attrs['start']
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self.end = attrs['end']
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if self.start >= self.end:
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raise Exception('start must be lower then end')
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self.description = attrs.get('description', '')
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self.properties = [
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PropertyAnnotation(x, self.tag_lookup[self.tag_id].properties)
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for x in attrs.get('properties', [])
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]
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for required_property_id in self.tag_lookup[self.tag_id].required_properties:
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if required_property_id not in self.properties:
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raise Exception('Missing required property: {}'.format(required_property_id))
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@property
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def name(self):
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return self.tag_lookup[self.tag_id].name
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def __lt__(self, other):
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if self.start == other.start:
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return self.name == 'token' and other.name != 'token'
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else:
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return self.start < other.start
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def __le__(self, other):
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if self.start == other.start:
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return self.name == 'token' or other.name != 'token'
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else:
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return self.start < other.start
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def __eq__(self, other):
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return self.start == other.start and self.name == other.name
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def __ne__(self, other):
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return self.start != other.start and self.name != other.name
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def __gt__(self, other):
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if self.start == other.start:
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return self.name != 'token' and other.name == 'token'
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else:
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return self.start > other.start
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def __ge__(self, other):
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if self.start == other.start:
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return self.name != 'token' or other.name == 'token'
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else:
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return self.start > other.start
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class PropertyAnnotation:
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def __init__(self, attrs, property_lookup):
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self.property_id = property['property_id']
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self.property_lookup = property_lookup
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if self.property_id not in self.property_lookup:
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raise Exception('Unknown property id: {}'.format(self.property_id))
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self.value = property['value']
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# TODO: Process attrs['possibleValues'] as self.labels (no id?)
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@property
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def name(self):
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return self.property_lookup[self.property_id].name
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class TagDefinition:
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def __init__(self, attrs):
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self.id = attrs['id']
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self.name = attrs['name']
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self.description = attrs.get('description', '')
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self.properties = {
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property_definition.id: property_definition
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for property_definition in [
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PropertyDefinition(x) for x in attrs.get('properties', [])
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]
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}
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@property
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def required_properties(self):
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return {property.id: property for property in self.properties
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if property.is_required}
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class PropertyDefinition:
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def __init__(self, attrs):
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self.id = attrs['id']
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self.name = attrs['name']
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self.description = attrs.get('description', '')
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self.flags = attrs.get('flags', [])
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self.labels = attrs.get('labels', [])
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@property
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def is_required(self):
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return 'required' in self.flags
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@property
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def has_multiple_values(self):
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return 'multiple' in self.flags
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47
packages/stand-off-data-py/stand_off_data/utils.py
Normal file
47
packages/stand-off-data-py/stand_off_data/utils.py
Normal file
@ -0,0 +1,47 @@
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def create_vrt(text, stand_off_data):
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# Devide annotations into CWB's verticalized text format (.vrt) logic
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p_attrs = [] # positional attributes
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s_attrs = [] # structural attributes
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for annotation in stand_off_data.annotations:
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if annotation.name == 'token':
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p_attrs.append(annotation)
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else:
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s_attrs.append(annotation)
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# Sort annotations, necessary for the next checks
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p_attrs.sort()
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s_attrs.sort()
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# Check for p_attr<->p_attr overlap
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for i, p_attr in enumerate(p_attrs[:-1]):
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next_p_attr = p_attrs[i + 1]
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# Check if first_p_attr starts/ends within second_p_attr
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if ((p_attr.start >= next_p_attr.start) and (p_attr.start <= next_p_attr.end) # noqa
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or (p_attr.end >= next_p_attr.start) and (p_attr.end <= next_p_attr.end)): # noqa
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raise Exception('Positional attribute overlaps another')
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# Check for s_attr<->p_attr overlap
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for i, s_attr in enumerate(s_attrs):
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for p_attr in p_attrs:
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# Check if s_attr starts within p_attr
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if s_attr.start > p_attr.start and s_attr.start < p_attr.end:
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# Change s_attr start to p_attr's start
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s_attrs[i].start = p_attr.start
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# Check if s_attr ends within p_attr
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if s_attr.end < p_attr.end and s_attr.end > p_attr.start:
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# Change s_attr end to p_attr's end
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s_attrs[i].end = p_attr.end
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# Check if s_attr starts/ends before/after p_attr
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if p_attr.start >= s_attr.end or p_attr.end <= s_attr.start:
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# No further Checking needed (just because p_attrs are sorted)
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break
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s_attr_start_buffer = {}
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s_attr_end_buffer = {}
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for i, s_attr in enumerate(s_attrs):
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if s_attr_start_buffer[s_attr.start]:
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s_attr_start_buffer[s_attr.start].append(i)
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else:
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s_attr_start_buffer[s_attr.start] = [i]
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if s_attr_end_buffer[s_attr.end]:
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s_attr_end_buffer[s_attr.end].append(i)
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else:
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s_attr_end_buffer[s_attr.end] = [1]
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vrt = ''
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# TODO do the work!
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251
spacy-nlp
251
spacy-nlp
@ -8,6 +8,14 @@ import json
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import os
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import spacy
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import textwrap
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import uuid
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def UUIDnopaque(name):
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return 'nopaque_{}'.format(
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uuid.uuid3(uuid.NAMESPACE_DNS,
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'{}@nopaque.sfb1288.uni-bielefeld.de'.format(name))
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)
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spacy_models = {spacy.info(pipeline)['lang']: pipeline
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@ -70,65 +78,167 @@ meta = {
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}
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}
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tags = {
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'token': {
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'description': '',
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'properties': {
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'lemma': {
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tags = [
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{
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'id': UUIDnopaque('token'),
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'name': 'token',
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'description': 'An individual token — i.e. a word, punctuation symbol, whitespace, etc.',
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'properties': [
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{
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'id': UUIDnopaque('token.lemma'),
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'name': 'lemma',
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'description': 'The base form of the word',
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'flags': ['required'],
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'tagset': None
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'labels': []
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},
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'pos': {
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{
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'id': UUIDnopaque('token.pos'),
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'name': 'pos',
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'description': 'The detailed part-of-speech tag',
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'flags': ['required'],
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'tagset': {label: spacy.explain(label) for label in spacy.info(model)['labels']['tagger']} # noqa
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'labels': [
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{
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'id': UUIDnopaque('token.pos={}'.format(label)),
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'name': label,
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'description': spacy.explain(label) or ''
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} for label in spacy.info(model)['labels']['tagger']
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]
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},
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'simple_pos': {
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{
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'id': UUIDnopaque('token.simple_pos'),
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'name': 'simple_pos',
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'description': 'The simple UPOS part-of-speech tag',
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'flags': ['required'],
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'tagset': {
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'ADJ': 'adjective',
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'ADP': 'adposition',
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'ADV': 'adverb',
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'AUX': 'auxiliary verb',
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'CONJ': 'coordinating conjunction',
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'DET': 'determiner',
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'INTJ': 'interjection',
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'NOUN': 'noun',
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'NUM': 'numeral',
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'PART': 'particle',
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'PRON': 'pronoun',
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'PROPN': 'proper noun',
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'PUNCT': 'punctuation',
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'SCONJ': 'subordinating conjunction',
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'SYM': 'symbol',
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'VERB': 'verb',
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'X': 'other'
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}
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'labels': [
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'ADJ',
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'description': 'adjective'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'ADP',
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'description': 'adposition'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'ADV',
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'description': 'adverb'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'AUX',
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'description': 'auxiliary verb'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'CONJ',
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'description': 'coordinating conjunction'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'DET',
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'description': 'determiner'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'INTJ',
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'description': 'interjection'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'NOUN',
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'description': 'noun'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'NUM',
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'description': 'numeral'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'PART',
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'description': 'particle'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'PRON',
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'description': 'pronoun'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'PROPN',
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'description': 'proper noun'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'PUNCT',
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'description': 'punctuation'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'SCONJ',
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'description': 'subordinating conjunction'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'SYM',
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'description': 'symbol'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'VERB',
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'description': 'verb'
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},
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{
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'id': UUIDnopaque('token.simple_pos=ADJ'),
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'name': 'X',
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'description': 'other'
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}
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]
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},
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'ner': {
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'description': 'Label indicating the type of the entity',
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'tagset': {label: spacy.explain(label) for label in spacy.info(model)['labels']['ner']} # noqa
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}
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}
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},
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's': {
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'description': 'Encodes the start and end of a sentence',
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'properties': None
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},
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'ent': {
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'description': 'Encodes the start and end of a named entity',
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'properties': {
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'type': {
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{
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'id': UUIDnopaque('token.ner'),
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'name': 'ner',
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'description': 'Label indicating the type of the entity',
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'flags': ['required'],
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'tagset': {label: spacy.explain(label) for label in spacy.info(model)['labels']['ner']} # noqa
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'labels': [
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{
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'id': UUIDnopaque('token.ner={}'.format(label)),
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'name': label,
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'description': spacy.explain(label) or ''
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} for label in spacy.info(model)['labels']['ner']
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]
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}
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}
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]
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},
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{
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'id': UUIDnopaque('s'),
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'name': 's',
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'description': 'Encodes the start and end of a sentence',
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'properties': []
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},
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{
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'id': UUIDnopaque('ent'),
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'name': 'ent',
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'description': 'Encodes the start and end of a named entity',
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'properties': [
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{
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'id': UUIDnopaque('ent.type'),
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'name': 'type',
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'description': 'Label indicating the type of the entity',
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'flags': ['required'],
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'labels': [
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{
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'id': UUIDnopaque('ent.type={}'.format(label)),
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'name': label,
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'description': spacy.explain(label) or ''
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} for label in spacy.info(model)['labels']['ner']
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]
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}
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]
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}
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}
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]
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annotations = []
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@ -142,27 +252,50 @@ while text_chunks:
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if token.is_sent_start:
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annotation = {'start': token.sent.start_char + chunk_offset,
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'end': token.sent.end_char + chunk_offset,
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'tag': 's'}
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'tag_id': UUIDnopaque('s'),
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'properties': []}
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annotations.append(annotation)
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# Check if the token is the start of an entity
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if token.ent_iob == 3:
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for ent_candidate in token.sent.ents:
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if ent_candidate.start_char == token.idx:
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ent = ent_candidate
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annotation = {'start': ent.start_char + chunk_offset,
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'end': ent.end_char + chunk_offset,
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'tag': 'ent',
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'properties': {'type': token.ent_type_}}
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annotation = {
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'start': ent.start_char + chunk_offset,
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'end': ent.end_char + chunk_offset,
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'tag_id': UUIDnopaque('ent'),
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'properties': [
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{
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'property_id': UUIDnopaque('ent.type'),
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'value': token.ent_type_
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}
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]
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}
|
||||
annotations.append(annotation)
|
||||
break
|
||||
annotation = {'start': token.idx + chunk_offset,
|
||||
'end': token.idx + len(token.text) + chunk_offset,
|
||||
'tag': 'token',
|
||||
'properties': {'pos': token.tag_,
|
||||
'lemma': token.lemma_,
|
||||
'simple_pos': token.pos_}}
|
||||
if token.ent_type_:
|
||||
annotation['properties']['ner'] = token.ent_type_
|
||||
annotation = {
|
||||
'start': token.idx + chunk_offset,
|
||||
'end': token.idx + len(token.text) + chunk_offset,
|
||||
'tag_id': UUIDnopaque('token'),
|
||||
'properties': [
|
||||
{
|
||||
'property_id': UUIDnopaque('token.pos'),
|
||||
'value': token.tag_
|
||||
},
|
||||
{
|
||||
'property_id': UUIDnopaque('token.lemma'),
|
||||
'value': token.lemma_
|
||||
},
|
||||
{
|
||||
'property_id': UUIDnopaque('token.simple_pos'),
|
||||
'value': token.pos_
|
||||
},
|
||||
{
|
||||
'property_id': UUIDnopaque('token.ner'),
|
||||
'value': token.ent_type_ if token.ent_type_ else 'None'
|
||||
}
|
||||
]
|
||||
}
|
||||
annotations.append(annotation)
|
||||
chunk_offset += len(text_chunk)
|
||||
text_chunk = None
|
||||
|
||||
Loading…
Reference in New Issue
Block a user