Triple

T14994469
Position Surface form Disambiguated ID Type / Status
Subject Senate of Bremen E373920 entity
Predicate hasJurisdictionOver P808 FINISHED
Object City of Bremen E76455 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 Bremen | Statement: [Senate of Bremen, hasJurisdictionOver, City of Bremen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Bremen
Context triple: [Senate of Bremen, hasJurisdictionOver, City of Bremen]
  • A. Bremen chosen
    Bremen is a city-state in northwestern Germany comprising the cities of Bremen and Bremerhaven, known for its historic Hanseatic heritage and major port on the Weser River.
  • B. Bremen
    Bremen is a small city in western Georgia, United States, known as a regional hub along major transportation routes and as part of the Atlanta metropolitan area’s outer region.
  • C. Bremen
    Bremen is a small village in Fairfield County, Ohio, known for its historic charm and tight-knit rural community.
  • 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. Friedeburg
    Friedeburg is a small municipality in Lower Saxony, Germany, known for its rural character and location within the East Frisian region.
  • 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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded716ebb481908224d2d4f7561b03 completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff0b3216fc8190b79740a993b98cb3 completed May 9, 2026, 10:23 a.m.
Created at: April 10, 2026, 2:53 a.m.