Triple

T7201091
Position Surface form Disambiguated ID Type / Status
Subject Bishopric of Hagen E168743 entity
Predicate hasCapital P204 FINISHED
Object Hagen E291575 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: Hagen | Statement: [Bishopric of Hagen, hasCapital, Hagen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hagen
Context triple: [Bishopric of Hagen, hasCapital, Hagen]
  • A. Hagen chosen
    Hagen is a city in the Ruhr region of North Rhine-Westphalia in western Germany, known historically as an industrial and transport hub.
  • B. Hagen
    Hagen is a surname of German origin borne by various notable individuals across fields such as music, sports, and academia.
  • C. Gescher
    Gescher is a small town in western Germany’s Münsterland region, noted for its traditional bell foundries and rural character.
  • D. Kleve
    Kleve is a historic town in western Germany near the Dutch border, known for its medieval castle and role as the former capital of the Duchy of Cleves.
  • 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_69c68a5376748190bb500f03df86e93e completed March 27, 2026, 1:46 p.m.
NER Named-entity recognition batch_69c6e94971508190bb38184c9af2fe51 completed March 27, 2026, 8:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69cd336af7c48190956add895fff9c21 completed April 1, 2026, 3:02 p.m.
Created at: March 27, 2026, 2:52 p.m.