Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
named-entity-recognition
Languages:
English
Size:
10K - 100K
License:
Update fabner.py with new tagging formats
Browse files
fabner.py
CHANGED
@@ -78,79 +78,60 @@ class FabNER(datasets.GeneratorBasedBuilder):
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# data = datasets.load_dataset('my_dataset', 'first_domain')
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# data = datasets.load_dataset('my_dataset', 'second_domain')
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(name="fabner", version=VERSION,
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]
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def _info(self):
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features = datasets.Features(
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{
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"id": datasets.Value("string"),
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"tokens": datasets.Sequence(datasets.Value("string")),
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"ner_tags": datasets.Sequence(
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datasets.features.ClassLabel(
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names=
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"O",
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"B-MATE", # Material
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"I-MATE",
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"O-MATE",
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"E-MATE",
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"S-MATE",
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"B-MANP", # Manufacturing Process
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"I-MANP",
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"O-MANP",
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"E-MANP",
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"S-MANP",
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"B-MACEQ", # Machine/Equipment
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"I-MACEQ",
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"O-MACEQ",
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"E-MACEQ",
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"S-MACEQ",
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"B-APPL", # Application
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"I-APPL",
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"O-APPL",
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"E-APPL",
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"S-APPL",
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"B-FEAT", # Engineering Features
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"I-FEAT",
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"O-FEAT",
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"E-FEAT",
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"S-FEAT",
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"B-PRO", # Mechanical Properties
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"I-PRO",
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"O-PRO",
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"E-PRO",
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"S-PRO",
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"B-CHAR", # Process Characterization
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"I-CHAR",
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"O-CHAR",
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"E-CHAR",
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"S-CHAR",
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"B-PARA", # Process Parameters
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"I-PARA",
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"O-PARA",
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"E-PARA",
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"S-PARA",
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"B-ENAT", # Enabling Technology
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"I-ENAT",
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"O-ENAT",
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"E-ENAT",
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"S-ENAT",
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"B-CONPRI", # Concept/Principles
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"I-CONPRI",
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"O-CONPRI",
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"E-CONPRI",
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"S-CONPRI",
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"B-MANS", # Manufacturing Standards
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"I-MANS",
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"O-MANS",
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"E-MANS",
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"S-MANS",
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"B-BIOP", # BioMedical
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"I-BIOP",
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"O-BIOP",
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"E-BIOP",
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"S-BIOP",
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]
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)
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),
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}
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@@ -203,7 +184,18 @@ class FabNER(datasets.GeneratorBasedBuilder):
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else:
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splits = line.split(" ")
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tokens.append(splits[0])
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# last example
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if tokens:
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yield guid, {
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# data = datasets.load_dataset('my_dataset', 'first_domain')
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# data = datasets.load_dataset('my_dataset', 'second_domain')
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(name="fabner", version=VERSION,
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description="The FabNER dataset with the original BIOES tagging format"),
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datasets.BuilderConfig(name="fabner_bio", version=VERSION,
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description="The FabNER dataset with BIO tagging format"),
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datasets.BuilderConfig(name="fabner_simple", version=VERSION,
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description="The FabNER dataset with no tagging format"),
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]
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DEFAULT_CONFIG_NAME = "fabner"
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def _info(self):
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entity_types = [
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"MATE", # Material
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"MANP", # Manufacturing Process
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"MACEQ", # Machine/Equipment
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"APPL", # Application
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"FEAT", # Engineering Features
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"PRO", # Mechanical Properties
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"CHAR", # Process Characterization
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"PARA", # Process Parameters
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"ENAT", # Enabling Technology
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"CONPRI", # Concept/Principles
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"MANS", # Manufacturing Standards
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"BIOP", # BioMedical
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]
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if self.config.name == "fabner":
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class_labels = ["O"]
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for entity_type in entity_types:
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class_labels.extend(
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[
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"B-" + entity_type,
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"I-" + entity_type,
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"O-" + entity_type,
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"E-" + entity_type,
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"S-" + entity_type,
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]
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)
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elif self.config.name == "fabner_bio":
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class_labels = ["O"]
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for entity_type in entity_types:
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class_labels.extend(
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[
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"B-" + entity_type,
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"I-" + entity_type,
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]
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)
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else:
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class_labels = ["O"] + entity_types
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features = datasets.Features(
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{
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"id": datasets.Value("string"),
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"tokens": datasets.Sequence(datasets.Value("string")),
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"ner_tags": datasets.Sequence(
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datasets.features.ClassLabel(
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names=class_labels
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)
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),
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}
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else:
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splits = line.split(" ")
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tokens.append(splits[0])
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ner_tag = splits[1].rstrip()
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if self.config.name == "fabner_simple":
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if ner_tag == "O":
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ner_tag = "O"
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else:
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ner_tag = ner_tag.split("-")[1]
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elif self.config.name == "fabner_bio":
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if ner_tag == "O":
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ner_tag = "O"
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else:
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ner_tag = ner_tag.replace("S-", "B-").replace("E-", "I-")
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ner_tags.append(ner_tag)
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# last example
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if tokens:
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yield guid, {
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