Triple

T8160785
Position Surface form Disambiguated ID Type / Status
Subject Cologne City Hall E190571 entity
Predicate ownedBy P347 FINISHED
Object City of Cologne E35950 NE FINISHED

How this triple was built (2 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: City of Cologne | Statement: [Cologne City Hall, ownedBy, City of Cologne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Cologne
Context triple: [Cologne City Hall, ownedBy, City of Cologne]
  • A. Imperial City of Cologne
    The Imperial City of Cologne was a major free imperial city of the Holy Roman Empire, renowned as a key commercial, religious, and cultural center on the Rhine.
  • B. Cologne chosen
    Cologne is a historic German city on the Rhine River, renowned for its Gothic cathedral, vibrant cultural scene, and status as a major economic and media hub.
  • C. Koblenz
    Koblenz is a historic German city in Rhineland-Palatinate, known for its strategic location at the confluence of the Rhine and Moselle rivers and its well-preserved fortresses and old town.
  • D. Old Town of Cologne
    The Old Town of Cologne is the historic city center along the Rhine, known for its medieval streets, traditional houses, and prominent Romanesque and Gothic churches.
  • E. City of Essen
    The City of Essen is a major urban center in Germany’s Ruhr area, historically significant as a medieval ecclesiastical seat and later as an important industrial and coal-mining hub.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca82bfeb6481909d07b91b5cf69f59 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb455559188190bf95d9d93bb76002 completed March 31, 2026, 3:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc6804a0c819091a6f46ef6c5670d completed April 2, 2026, 1:29 a.m.
Created at: March 30, 2026, 5:38 p.m.