Commit
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67a4e57
1
Parent(s):
8a1283f
use BRAT document types from pie-datasets
Browse files- brat.py +7 -28
- requirements.txt +1 -1
brat.py
CHANGED
@@ -1,14 +1,17 @@
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import dataclasses
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import logging
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from collections import defaultdict
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from typing import Any, Dict, List, Optional, Tuple, Union
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import datasets
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from pytorch_ie.annotations import BinaryRelation, LabeledMultiSpan, LabeledSpan
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from pytorch_ie.core import Annotation
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from pytorch_ie.documents import TextBasedDocument
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from pie_datasets import GeneratorBasedBuilder
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logger = logging.getLogger(__name__)
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@@ -24,33 +27,9 @@ def ld2dl(
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return {k: [dic[k] for dic in list_fo_dicts] for k in keys}
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@dataclasses.dataclass(eq=True, frozen=True)
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class Attribute(Annotation):
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annotation: Annotation
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label: str
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value: Optional[str] = None
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score: Optional[float] = dataclasses.field(default=None, compare=False)
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@dataclasses.dataclass
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class BratDocument(TextBasedDocument):
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spans: AnnotationList[LabeledMultiSpan] = annotation_field(target="text")
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relations: AnnotationList[BinaryRelation] = annotation_field(target="spans")
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span_attributes: AnnotationList[Attribute] = annotation_field(target="spans")
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relation_attributes: AnnotationList[Attribute] = annotation_field(target="relations")
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@dataclasses.dataclass
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class BratDocumentWithMergedSpans(TextBasedDocument):
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spans: AnnotationList[LabeledSpan] = annotation_field(target="text")
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relations: AnnotationList[BinaryRelation] = annotation_field(target="spans")
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span_attributes: AnnotationList[Attribute] = annotation_field(target="spans")
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relation_attributes: AnnotationList[Attribute] = annotation_field(target="relations")
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def example_to_document(
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example: Dict[str, Any], merge_fragmented_spans: bool = False
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) -> BratDocument:
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if merge_fragmented_spans:
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doc = BratDocumentWithMergedSpans(text=example["context"], id=example["file_name"])
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else:
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import logging
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from collections import defaultdict
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from typing import Any, Dict, List, Optional, Tuple, Union
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import datasets
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from pytorch_ie.annotations import BinaryRelation, LabeledMultiSpan, LabeledSpan
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from pytorch_ie.core import Annotation
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from pie_datasets import GeneratorBasedBuilder
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from pie_datasets.document.types import (
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Attribute,
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BratDocument,
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BratDocumentWithMergedSpans,
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)
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logger = logging.getLogger(__name__)
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return {k: [dic[k] for dic in list_fo_dicts] for k in keys}
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def example_to_document(
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example: Dict[str, Any], merge_fragmented_spans: bool = False
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) -> Union[BratDocument, BratDocumentWithMergedSpans]:
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if merge_fragmented_spans:
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doc = BratDocumentWithMergedSpans(text=example["context"], id=example["file_name"])
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else:
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requirements.txt
CHANGED
@@ -1 +1 @@
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pie-datasets>=0.3.
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pie-datasets>=0.3.1
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