Triple
T1765929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blaustein |
E38762
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Wippingen
Wippingen is a village and district (Ortsteil) of the municipality of Blaustein in the Alb-Donau district of Baden-Württemberg, Germany.
|
E244095
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Wippingen | Statement: [Blaustein, hasSubdivision, Wippingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wippingen Context triple: [Blaustein, hasSubdivision, Wippingen]
-
A.
Tureberg
Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
-
B.
Briesen
Briesen is a small town in present-day Germany best known as the birthplace of Nobel Prize–winning chemist Walther Nernst.
-
C.
Wienhausen
Wienhausen is a historic village in Lower Saxony, Germany, best known for its medieval Cistercian nunnery and well-preserved half-timbered architecture.
-
D.
Weiterstadt
Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
-
E.
Göhren
Göhren is a seaside resort town on the Baltic Sea coast of Germany, located on the island of Rügen and known for its beaches and tourism.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wippingen Triple: [Blaustein, hasSubdivision, Wippingen]
Generated description
Wippingen is a village and district (Ortsteil) of the municipality of Blaustein in the Alb-Donau district of Baden-Württemberg, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wippingen Target entity description: Wippingen is a village and district (Ortsteil) of the municipality of Blaustein in the Alb-Donau district of Baden-Württemberg, Germany.
-
A.
Tureberg
Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
-
B.
Briesen
Briesen is a small town in present-day Germany best known as the birthplace of Nobel Prize–winning chemist Walther Nernst.
-
C.
Wienhausen
Wienhausen is a historic village in Lower Saxony, Germany, best known for its medieval Cistercian nunnery and well-preserved half-timbered architecture.
-
D.
Weiterstadt
Weiterstadt is a town in the German state of Hesse, located near Darmstadt and known for its residential areas and commercial centers.
-
E.
Göhren
Göhren is a seaside resort town on the Baltic Sea coast of Germany, located on the island of Rügen and known for its beaches and tourism.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a8862d562481908d7025a1c1f67c0d |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa6467c3f08190abc8a06269ede908 |
completed | March 6, 2026, 5:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae651c82588190b9f1461a7e135670 |
completed | March 9, 2026, 6:13 a.m. |
| NEDg | Description generation | batch_69ae65ac14a8819091fa0795c7f99917 |
completed | March 9, 2026, 6:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae66429c208190ae011d7ee001c9ea |
completed | March 9, 2026, 6:18 a.m. |
Created at: March 4, 2026, 7:31 p.m.