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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):
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):
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],
relation_label: datasets.ClassLabel,
proposition_label: datasets.ClassLabel,
):
document = CDCPDocument(id=example["id"], text=example["text"])
for proposition_dict in dl2ld(example["propositions"]):
proposition = LabeledSpan(
start=proposition_dict["start"],
end=proposition_dict["end"],
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(
head=document.propositions[relation_dict["head"]],
tail=document.propositions[relation_dict["tail"]],
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:
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,
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" # type: ignore
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
)
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