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from https://github.com/ArneBinder/pie-datasets/pull/134

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also contains the fix https://github.com/ArneBinder/pie-datasets/pull/139

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  1. README.md +34 -0
  2. biorel.py +122 -0
  3. requirements.txt +1 -0
README.md ADDED
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+ # PIE Dataset Card for "BioRel"
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+
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+ This is a [PyTorch-IE](https://github.com/ChristophAlt/pytorch-ie) wrapper for the
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+ [BioRel Huggingface dataset loading script](https://huggingface.co/datasets/DFKI-SLT/BioRel).
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+
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+ ## Data Schema
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+
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+ The document type for this dataset is `BioRelDocument` which defines the following data fields:
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+
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+ - `text` (str)
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+
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+ and the following annotation layers:
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+
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+ - `entities` (annotation type: `SpanWithIdAndName`, target: `text`)
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+ - `relations` (annotation type: `BinaryRelation`, target: `entities`)
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+
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+ `SpanWithIdAndName` is a custom annotation type that extends typical `Span` with the following data fields:
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+
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+ - `id` (str, for entity identification)
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+ - `name` (str, entity string between span start and end)
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+
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+ See [here](https://github.com/ArneBinder/pie-modules/blob/main/src/pie_modules/annotations.py) and
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+ [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/annotations.py) for the annotation
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+ type definitions.
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+
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+ ## Document Converters
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+
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+ The dataset provides predefined document converters for the following target document types:
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+
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+ - `pie_modules.documents.TextDocumentWithLabeledSpansAndBinaryRelations`
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+
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+ See [here](https://github.com/ArneBinder/pie-modules/blob/main/src/pie_modules/documents.py) and
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+ [here](https://github.com/ChristophAlt/pytorch-ie/blob/main/src/pytorch_ie/documents.py) for the document type
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+ definitions.
biorel.py ADDED
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+ import dataclasses
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+ import logging
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+ from typing import Any
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+
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+ import datasets
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+ from pytorch_ie import AnnotationLayer, annotation_field
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+ from pytorch_ie.annotations import BinaryRelation, LabeledSpan, Span
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+ from pytorch_ie.documents import (
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+ TextBasedDocument,
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+ TextDocumentWithLabeledSpansAndBinaryRelations,
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+ )
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+
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+ from pie_datasets import ArrowBasedBuilder, GeneratorBasedBuilder
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+
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+ logger = logging.getLogger(__name__)
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+ warning_counter = 0
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+
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+
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+ @dataclasses.dataclass(frozen=True)
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+ class SpanWithIdAndName(Span):
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+ id: str
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+ name: str
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+
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+ def resolve(self) -> Any:
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+ return self.id, self.name, super().resolve()
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+
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+
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+ @dataclasses.dataclass
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+ class BioRelDocument(TextBasedDocument):
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+ entities: AnnotationLayer[SpanWithIdAndName] = annotation_field(target="text")
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+ relations: AnnotationLayer[BinaryRelation] = annotation_field(target="entities")
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+
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+
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+ def example_to_document(example) -> BioRelDocument:
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+ document = BioRelDocument(text=example["text"])
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+ head = SpanWithIdAndName(
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+ id=example["h"]["id"],
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+ name=example["h"]["name"],
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+ start=example["h"]["pos"][0],
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+ end=example["h"]["pos"][1],
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+ )
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+ tail = SpanWithIdAndName(
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+ id=example["t"]["id"],
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+ name=example["t"]["name"],
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+ start=example["t"]["pos"][0],
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+ end=example["t"]["pos"][1],
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+ )
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+ document.entities.extend([head, tail])
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+
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+ relation = BinaryRelation(head=head, tail=tail, label=example["relation"])
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+ document.relations.append(relation)
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+ return document
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+
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+
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+ def document_to_example(document):
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+ head = document.entities[0]
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+ tail = document.entities[1]
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+ return {
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+ "text": document.text,
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+ "relation": document.relations[0].label,
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+ "h": {"id": head.id, "name": head.name, "pos": [head.start, head.end]},
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+ "t": {"id": tail.id, "name": tail.name, "pos": [tail.start, tail.end]},
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+ }
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+
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+
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+ def convert_to_text_document_with_labeled_spans_and_binary_relations(
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+ document: BioRelDocument,
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+ ) -> TextDocumentWithLabeledSpansAndBinaryRelations:
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+ text_document = TextDocumentWithLabeledSpansAndBinaryRelations(text=document.text)
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+ old2new_spans = {}
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+ ids = []
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+ names = []
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+
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+ for entity in document.entities: # in our case two entities (head and tail)
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+ # create LabeledSpan and append
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+ labeled_span = LabeledSpan(start=entity.start, end=entity.end, label="ENTITY")
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+ text_document.labeled_spans.append(labeled_span)
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+
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+ # Map the original entity to the new labeled span
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+ old2new_spans[entity] = labeled_span
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+
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+ ids.append(entity.id)
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+ names.append(entity.name)
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+
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+ if len(document.relations) != 1: # one relation between two entities
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+ raise ValueError(f"Expected exactly one relation, got {len(document.relations)}")
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+ old_rel = document.relations[0]
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+
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+ # create BinaryRelation and append
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+ rel = BinaryRelation(
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+ head=old2new_spans[old_rel.head],
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+ tail=old2new_spans[old_rel.tail],
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+ label=old_rel.label,
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+ )
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+ text_document.binary_relations.append(rel)
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+ text_document.metadata["entity_ids"] = ids
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+ text_document.metadata["entity_names"] = names
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+
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+ return text_document
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+
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+
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+ class BioRel(ArrowBasedBuilder):
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+ DOCUMENT_TYPE = BioRelDocument
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+ BASE_DATASET_PATH = "DFKI-SLT/BioRel"
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+ BASE_DATASET_REVISION = "e4869c484c582cfbc7ead10d4d421bd4b275fa4e"
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+
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+ BUILDER_CONFIGS = [
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+ datasets.BuilderConfig(
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+ version=datasets.Version("1.0.0"),
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+ description="BioRel dataset",
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+ )
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+ ]
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+
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+ DOCUMENT_CONVERTERS = {
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+ TextDocumentWithLabeledSpansAndBinaryRelations: convert_to_text_document_with_labeled_spans_and_binary_relations
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+ }
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+
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+ def _generate_document(self, example, **kwargs):
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+ return example_to_document(example)
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+
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+ def _generate_example(self, document: BioRelDocument, **kwargs):
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+ return document_to_example(document)
requirements.txt ADDED
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+ pie-datasets>=0.6.0,<0.11.0