| import dataclasses
|
| import logging
|
| from typing import Any, Dict, List, Optional
|
|
|
| import datasets
|
| from pie_core import Annotation, AnnotationLayer, annotation_field
|
| from pie_documents.annotations import BinaryRelation, LabeledSpan
|
| from pie_documents.document.processing.text_span_trimmer import trim_text_spans
|
| from pie_documents.documents import (
|
| TextBasedDocument,
|
| TextDocumentWithLabeledSpansAndBinaryRelations,
|
| )
|
|
|
| from pie_datasets import GeneratorBasedBuilder
|
|
|
| log = logging.getLogger(__name__)
|
|
|
|
|
| def dl2ld(dict_of_lists):
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| return [dict(zip(dict_of_lists, t)) for t in zip(*dict_of_lists.values())]
|
|
|
|
|
| def ld2dl(list_of_dicts, keys: Optional[List[str]] = None):
|
| return {k: [d[k] for d in list_of_dicts] for k in keys}
|
|
|
|
|
| @dataclasses.dataclass(frozen=True)
|
| class Attribute(Annotation):
|
| value: str
|
| annotation: Annotation
|
|
|
|
|
| @dataclasses.dataclass
|
| class CDCPDocument(TextBasedDocument):
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| propositions: AnnotationLayer[LabeledSpan] = annotation_field(target="text")
|
| relations: AnnotationLayer[BinaryRelation] = annotation_field(target="propositions")
|
| urls: AnnotationLayer[Attribute] = annotation_field(target="propositions")
|
|
|
|
|
| def example_to_document(
|
| example: Dict[str, Any],
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| relation_label: datasets.ClassLabel,
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| proposition_label: datasets.ClassLabel,
|
| ):
|
| document = CDCPDocument(id=example["id"], text=example["text"])
|
| for proposition_dict in dl2ld(example["propositions"]):
|
| proposition = LabeledSpan(
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| start=proposition_dict["start"],
|
| end=proposition_dict["end"],
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| label=proposition_label.int2str(proposition_dict["label"]),
|
| )
|
| document.propositions.append(proposition)
|
| if proposition_dict.get("url", "") != "":
|
| url = Attribute(annotation=proposition, value=proposition_dict["url"])
|
| document.urls.append(url)
|
|
|
| for relation_dict in dl2ld(example["relations"]):
|
| relation = BinaryRelation(
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| head=document.propositions[relation_dict["head"]],
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| tail=document.propositions[relation_dict["tail"]],
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| label=relation_label.int2str(relation_dict["label"]),
|
| )
|
| document.relations.append(relation)
|
|
|
| return document
|
|
|
|
|
| def document_to_example(
|
| document: CDCPDocument,
|
| relation_label: datasets.ClassLabel,
|
| proposition_label: datasets.ClassLabel,
|
| ) -> Dict[str, Any]:
|
| result = {"id": document.id, "text": document.text}
|
| proposition2dict = {}
|
| proposition2idx = {}
|
| for idx, proposition in enumerate(document.propositions):
|
| proposition2dict[proposition] = {
|
| "start": proposition.start,
|
| "end": proposition.end,
|
| "label": proposition_label.str2int(proposition.label),
|
| "url": "",
|
| }
|
| proposition2idx[proposition] = idx
|
| for url in document.urls:
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| proposition2dict[url.annotation]["url"] = url.value
|
|
|
| result["propositions"] = ld2dl(
|
| proposition2dict.values(), keys=["start", "end", "label", "url"]
|
| )
|
|
|
| relations = [
|
| {
|
| "head": proposition2idx[relation.head],
|
| "tail": proposition2idx[relation.tail],
|
| "label": relation_label.str2int(relation.label),
|
| }
|
| for relation in document.relations
|
| ]
|
| result["relations"] = ld2dl(relations, keys=["head", "tail", "label"])
|
|
|
| return result
|
|
|
|
|
| def convert_to_text_document_with_labeled_spans_and_binary_relations(
|
| document: CDCPDocument,
|
| verbose: bool = True,
|
| ) -> TextDocumentWithLabeledSpansAndBinaryRelations:
|
| doc_simplified = document.as_type(
|
| TextDocumentWithLabeledSpansAndBinaryRelations,
|
| field_mapping={"propositions": "labeled_spans", "relations": "binary_relations"},
|
| )
|
| result = trim_text_spans(
|
| doc_simplified,
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| layer="labeled_spans",
|
| verbose=verbose,
|
| )
|
| return result
|
|
|
|
|
| class CDCP(GeneratorBasedBuilder):
|
| DOCUMENT_TYPE = CDCPDocument
|
|
|
| DOCUMENT_CONVERTERS = {
|
| TextDocumentWithLabeledSpansAndBinaryRelations: convert_to_text_document_with_labeled_spans_and_binary_relations
|
| }
|
|
|
| BASE_DATASET_PATH = "DFKI-SLT/cdcp"
|
| BASE_DATASET_REVISION = "3cf79257900b3f97e4b8f9faae2484b1a534f484"
|
|
|
| BUILDER_CONFIGS = [datasets.BuilderConfig(name="default")]
|
|
|
| DEFAULT_CONFIG_NAME = "default"
|
|
|
| def _generate_document_kwargs(self, dataset):
|
| return {
|
| "relation_label": dataset.features["relations"].feature["label"],
|
| "proposition_label": dataset.features["propositions"].feature["label"],
|
| }
|
|
|
| def _generate_document(self, example, relation_label, proposition_label):
|
| return example_to_document(
|
| example, relation_label=relation_label, proposition_label=proposition_label
|
| )
|
|
|
