Triple

T13278096
Position Surface form Disambiguated ID Type / Status
Subject Ausgleich E316244 entity
Predicate tookPlaceIn P40 FINISHED
Object Pest-Buda E840043 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: Pest-Buda | Statement: [Ausgleich, tookPlaceIn, Pest-Buda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pest-Buda
Context triple: [Ausgleich, tookPlaceIn, Pest-Buda]
  • A. Pest-Buda chosen
    Pest-Buda was the historic twin-city on the banks of the Danube—comprising Pest and Buda—that served as a political and cultural center of Hungary before its unification into modern Budapest.
  • B. Bubas
    Bubas is a surname most notably associated with Vic Bubas, a prominent American college basketball coach.
  • C. Pütürge
    Pütürge is a rural district and town in eastern Turkey known for its mountainous terrain and traditional Anatolian village life.
  • D. Barbula
    Barbula was a cognomen of the ancient Roman gens Aemilia, borne by several members of this prominent patrician family.
  • E. Eperjes
    Eperjes is a historic town in present-day Slovakia, known today as Prešov, which was one of the major urban centers of the former Upper Hungary 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_69d806b349908190a9a61dd9323bf153 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99043fba88190872ede6f63e2fbcb completed April 11, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69f70a56fa048190b32dcef31b978d9c completed May 3, 2026, 8:41 a.m.
Created at: April 9, 2026, 9:26 p.m.