from https://github.com/ArneBinder/pie-datasets/pull/150

drugprot.py

@@ -30,7 +30,7 @@ class DrugprotBigbioDocument(TextBasedDocument):
 
 
 def example2drugprot(example: Dict[str, Any]) -> DrugprotDocument:
-    metadata = {"entity_ids": []}
+    metadata = {"entity_ids": [], "relation_ids": []}
     id2labeled_span: Dict[str, LabeledSpan] = {}
 
     document = DrugprotDocument(
@@ -40,6 +40,7 @@ def example2drugprot(example: Dict[str, Any]) -> DrugprotDocument:
         id=example["document_id"],
         metadata=metadata,
     )
+
     for span in example["entities"]:
         labeled_span = LabeledSpan(
             start=span["offset"][0],
@@ -47,23 +48,30 @@ def example2drugprot(example: Dict[str, Any]) -> DrugprotDocument:
             label=span["type"],
         )
         document.entities.append(labeled_span)
-        document.metadata["entity_ids"].append(span["id"])
-        id2labeled_span[span["id"]] = labeled_span
+        entity_id = span["id"].split("_")[1]
+        document.metadata["entity_ids"].append(entity_id)
+        id2labeled_span[entity_id] = labeled_span
+
     for relation in example["relations"]:
+        arg1_id = relation["arg1_id"].split("_")[1]
+        arg2_id = relation["arg2_id"].split("_")[1]
         document.relations.append(
             BinaryRelation(
-                head=id2labeled_span[relation["arg1_id"]],
-                tail=id2labeled_span[relation["arg2_id"]],
+                head=id2labeled_span[arg1_id],
+                tail=id2labeled_span[arg2_id],
                 label=relation["type"],
             )
         )
+        relation_id = "R" + relation["id"].split("_")[1]
+        document.metadata["relation_ids"].append(relation_id)
+
     return document
 
 
 def example2drugprot_bigbio(example: Dict[str, Any]) -> DrugprotBigbioDocument:
     text = " ".join([" ".join(passage["text"]) for passage in example["passages"]])
     doc_id = example["document_id"]
-    metadata = {"entity_ids": []}
+    metadata = {"entity_ids": [], "relation_ids": []}
     id2labeled_span: Dict[str, LabeledSpan] = {}
 
     document = DrugprotBigbioDocument(
@@ -79,7 +87,7 @@ def example2drugprot_bigbio(example: Dict[str, Any]) -> DrugprotBigbioDocument:
                 label=passage["type"],
             )
         )
-    # We sort labels and relation to always have an deterministic order for testing purposes.
+    # We sort labels and relation to always have a deterministic order for testing purposes.
     for span in example["entities"]:
         labeled_span = LabeledSpan(
             start=span["offsets"][0][0],
@@ -87,19 +95,114 @@ def example2drugprot_bigbio(example: Dict[str, Any]) -> DrugprotBigbioDocument:
             label=span["type"],
         )
         document.entities.append(labeled_span)
-        document.metadata["entity_ids"].append(span["id"])
-        id2labeled_span[span["id"]] = labeled_span
+        entity_id = span["id"].split("_")[1]
+        document.metadata["entity_ids"].append(entity_id)
+        id2labeled_span[entity_id] = labeled_span
+
     for relation in example["relations"]:
+        arg1_id = relation["arg1_id"].split("_")[1]
+        arg2_id = relation["arg2_id"].split("_")[1]
         document.relations.append(
             BinaryRelation(
-                head=id2labeled_span[relation["arg1_id"]],
-                tail=id2labeled_span[relation["arg2_id"]],
+                head=id2labeled_span[arg1_id],
+                tail=id2labeled_span[arg2_id],
                 label=relation["type"],
             )
         )
+        relation_id = "R" + relation["id"].split("_")[1]
+        document.metadata["relation_ids"].append(relation_id)
+
     return document
 
 
+def drugprot2example(doc: DrugprotDocument) -> Dict[str, Any]:
+    entities = []
+    for i, entity in enumerate(doc.entities):
+        entities.append(
+            {
+                "id": doc.id + "_" + doc.metadata["entity_ids"][i],
+                "type": entity.label,
+                "text": doc.text[entity.start : entity.end],
+                "offset": [entity.start, entity.end],
+            }
+        )
+
+    relations = []
+    for i, relation in enumerate(doc.relations):
+        relations.append(
+            {
+                "id": doc.id + "_" + doc.metadata["relation_ids"][i][1:],
+                "arg1_id": doc.id
+                + "_"
+                + doc.metadata["entity_ids"][doc.entities.index(relation.head)],
+                "arg2_id": doc.id
+                + "_"
+                + doc.metadata["entity_ids"][doc.entities.index(relation.tail)],
+                "type": relation.label,
+            }
+        )
+
+    return {
+        "document_id": doc.id,
+        "title": doc.title,
+        "abstract": doc.abstract,
+        "text": doc.text,
+        "entities": entities,
+        "relations": relations,
+    }
+
+
+def drugprot_bigbio2example(doc: DrugprotBigbioDocument) -> Dict[str, Any]:
+    entities = []
+    for i, entity in enumerate(doc.entities):
+        entities.append(
+            {
+                "id": doc.id + "_" + doc.metadata["entity_ids"][i],
+                "normalized": [],
+                "offsets": [[entity.start, entity.end]],
+                "type": entity.label,
+                "text": [doc.text[entity.start : entity.end]],
+            }
+        )
+
+    relations = []
+    for i, relation in enumerate(doc.relations):
+        relations.append(
+            {
+                "id": doc.id + "_" + doc.metadata["relation_ids"][i][1:],
+                "arg1_id": doc.id
+                + "_"
+                + doc.metadata["entity_ids"][doc.entities.index(relation.head)],
+                "arg2_id": doc.id
+                + "_"
+                + doc.metadata["entity_ids"][doc.entities.index(relation.tail)],
+                "normalized": [],
+                "type": relation.label,
+            }
+        )
+
+    passages = []
+    for passage in doc.passages:
+        passages.append(
+            {
+                "id": doc.id + "_" + passage.label,
+                "text": [doc.text[passage.start : passage.end]],
+                "offsets": [[passage.start, passage.end]],
+                "type": passage.label,
+            }
+        )
+
+    return {
+        "coreferences": [],
+        "document_id": doc.id,
+        "entities": entities,
+        "events": [],
+        "id": doc.id,
+        "passages": passages,
+        "relations": relations,
+    }
+
+
 class Drugprot(GeneratorBasedBuilder):
     DOCUMENT_TYPES = {
         "drugprot_source": DrugprotDocument,
@@ -144,8 +247,7 @@ class Drugprot(GeneratorBasedBuilder):
             raise ValueError(f"Unknown dataset name: {self.config.name}")
 
     def _generate_document(
-        self,
-        example: Dict[str, Any],
+        self, example: Dict[str, Any], **kwargs
     ) -> Union[DrugprotDocument, DrugprotBigbioDocument]:
         if self.config.name == "drugprot_source":
             return example2drugprot(example)
@@ -153,3 +255,13 @@ class Drugprot(GeneratorBasedBuilder):
             return example2drugprot_bigbio(example)
         else:
             raise ValueError(f"Unknown dataset config name: {self.config.name}")
+
+    def _generate_example(
+        self, document: Union[DrugprotDocument, DrugprotBigbioDocument], **kwargs
+    ) -> Dict[str, Any]:
+        if isinstance(document, DrugprotBigbioDocument):
+            return drugprot_bigbio2example(document)
+        elif isinstance(document, DrugprotDocument):
+            return drugprot2example(document)
+        else:
+            raise ValueError(f"Unknown document type: {type(document)}")