add DOCUMENT_CONVERTERS

conll2012_ontonotesv5.py

@@ -1,12 +1,12 @@
 import dataclasses
-import itertools
 from collections import defaultdict
 from typing import Any, Callable, Dict, List, Optional, Tuple
 
 import datasets
 import pytorch_ie
-from pytorch_ie.annotations import BinaryRelation, LabeledSpan, NaryRelation, Span
+from pytorch_ie.annotations import LabeledSpan, NaryRelation, Span
 from pytorch_ie.core import Annotation, AnnotationList, Document, annotation_field
+from pytorch_ie.documents import TextDocumentWithLabeledEntitiesAndLabeledPartitions
 
 
 @dataclasses.dataclass(eq=True, frozen=True)
@@ -229,6 +229,42 @@ def example_to_document(
     return doc
 
 
+def token_based_document_with_entities_and_sentences_to_text_based(
+    doc: Conll2012OntonotesV5Document,
+    token_separator: str = " ",
+) -> TextDocumentWithLabeledEntitiesAndLabeledPartitions:
+    start = 0
+    token_offsets: List[Tuple[int, int]] = []
+    for token in doc.tokens:
+        end = start + len(token)
+        token_offsets.append((start, end))
+        # we add the separator after each token
+        start = end + len(token_separator)
+
+    text = token_separator.join([token for token in doc.tokens])
+
+    entity_map: Dict[Tuple[int, int], LabeledSpan] = {}
+
+    for entity in doc.entities:
+        char_start = token_offsets[entity.start][0]
+        char_end = token_offsets[entity.end - 1][1]
+        char_offset_entity = LabeledSpan(start=char_start, end=char_end, label=entity.label)
+        entity_map[(entity.start, entity.end)] = char_offset_entity
+
+    sentence_map: Dict[Tuple[int, int], LabeledSpan] = {}
+    for sentence in doc.sentences:
+        char_start = token_offsets[sentence.start][0]
+        char_end = token_offsets[sentence.end - 1][1]
+        char_offset_sentence = LabeledSpan(start=char_start, end=char_end, label="sentence")
+        sentence_map[(sentence.start, sentence.end)] = char_offset_sentence
+
+    new_doc = TextDocumentWithLabeledEntitiesAndLabeledPartitions(text=text, id=doc.id)
+    new_doc.entities.extend(entity_map.values())
+    new_doc.partitions.extend(sentence_map.values())
+
+    return new_doc
+
+
 class Conll2012OntonotesV5Config(datasets.BuilderConfig):
     """BuilderConfig for the CoNLL formatted OntoNotes dataset."""
 
@@ -257,6 +293,10 @@ class Conll2012OntonotesV5Config(datasets.BuilderConfig):
 class Conll2012Ontonotesv5(pytorch_ie.data.builder.GeneratorBasedBuilder):
     DOCUMENT_TYPE = Conll2012OntonotesV5Document
 
+    DOCUMENT_CONVERTERS = {
+        TextDocumentWithLabeledEntitiesAndLabeledPartitions: token_based_document_with_entities_and_sentences_to_text_based
+    }
+
     BASE_DATASET_PATH = "DFKI-SLT/conll2012_ontonotesv5"
 
     BUILDER_CONFIGS = [