Triple

T12600501
Position Surface form Disambiguated ID Type / Status
Subject Wuppertal District Court E300843 entity
Predicate hasSeat P3522 FINISHED
Object city of Wuppertal E173299 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 Wuppertal | Statement: [Wuppertal District Court, hasSeat, city of Wuppertal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Wuppertal
Context triple: [Wuppertal District Court, hasSeat, city of Wuppertal]
  • A. Wuppertal chosen
    Wuppertal is a city in western Germany known for its steep slopes, extensive parks, and the unique suspended monorail Wuppertal Schwebebahn.
  • B. 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.
  • C. Mülheim an der Ruhr
    Mülheim an der Ruhr is a city in western Germany’s Ruhr area, known for its industrial heritage, riverside setting on the Ruhr River, and role as a regional economic and cultural center.
  • D. City of Wesel
    The City of Wesel is a historic German town on the Lower Rhine that became an important Reformation and trading center in the early modern period.
  • E. Recklinghausen
    Recklinghausen is a city in the Ruhr area of North Rhine-Westphalia, western Germany, known historically for coal mining and its role as a regional administrative center.
  • 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954d1f6ac8190ab21ca7bcbc80129 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcb63c80048190be87b41cdd4ac775 completed May 7, 2026, 3:56 p.m.
Created at: April 9, 2026, 5:09 p.m.