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a221720 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | from datasets import Dataset, DatasetDict
import spacy
from spacy.tokens import DocBin
from pathlib import Path
nlp = spacy.blank("da")
corpus_path = Path("corpus/cdt_ddt")
def docbin_to_rows(path):
doc_bin = DocBin().from_disk(path)
rows = []
for doc in doc_bin.get_docs(nlp.vocab):
row = doc.to_json()
row.pop("spans", None) # dropped the key variable dictionaries to replace with a list representing the clusters
row["coref_clusters"] = [
[{"start": span.start_char, "end": span.end_char, "label": span.label_}
for span in doc.spans[key]]
for key in sorted(doc.spans.keys())
if key.startswith("coref_clusters_")
]
rows.append(row)
return rows
dataset = DatasetDict({
"train": Dataset.from_list(docbin_to_rows(corpus_path/"train.spacy")),
"dev": Dataset.from_list(docbin_to_rows(corpus_path/"dev.spacy")),
"test": Dataset.from_list(docbin_to_rows(corpus_path/"test.spacy")),
})
dataset.push_to_hub("johanamayer/cdt_ddt_union") |