Upload conll2003.py

conll2003.py

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+from dataclasses import dataclass
+
+import pytorch_ie.data.builder
+from pytorch_ie.annotations import AnnotationList, LabeledSpan
+from pytorch_ie.document import TextDocument, annotation_field
+
+# import tests.data.test_new_document_and_datasets
+from pytorch_ie.utils.span import bio_tags_to_spans
+
+# from tests.data.test_new_document_and_datasets import (
+#     AnnotationList,
+#     Document,
+#     LabeledSpan,
+#     annotation_field,
+# )
+
+
+@dataclass
+class CoNLL2003Document(TextDocument):
+    entities: AnnotationList[LabeledSpan] = annotation_field(target="text")
+
+
+class Conll2003(pytorch_ie.data.builder.GeneratorBasedBuilder):
+    DOCUMENT_TYPE = CoNLL2003Document
+
+    BASE_PATH = "conll2003"
+
+    def _generate_document_kwargs(self, dataset):
+        return {"int_to_str": dataset.features["ner_tags"].feature.int2str}
+
+    def _generate_document(self, example, int_to_str):
+        doc_id = example["id"]
+        tokens = example["tokens"]
+        ner_tags = example["ner_tags"]
+
+        start = 0
+        token_offsets = []
+        tag_sequence = []
+        for token, tag_id in zip(tokens, ner_tags):
+            end = start + len(token)
+            token_offsets.append((start, end))
+            tag_sequence.append(int_to_str(tag_id))
+
+            start = end + 1
+
+        text = " ".join(tokens)
+        spans = bio_tags_to_spans(tag_sequence)
+
+        document = CoNLL2003Document(text=text, id=doc_id)
+
+        for label, (start, end) in spans:
+            start_offset = token_offsets[start][0]
+            end_offset = token_offsets[end][1]
+            document.entities.append(LabeledSpan(start=start_offset, end=end_offset, label=label))
+
+        return document