Triple

T11704125
Position Surface form Disambiguated ID Type / Status
Subject Felvidék E278196 entity
Predicate hasImportantMiningTown P14082 FINISHED
Object Rozsnyó E1034078 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: Rozsnyó | Statement: [Felvidék, hasImportantMiningTown, Rozsnyó]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rozsnyó
Context triple: [Felvidék, hasImportantMiningTown, Rozsnyó]
  • A. Rozsnyó chosen
    Rozsnyó is a historic town in present-day Slovakia, known for its medieval center and long-standing cultural significance within the Felvidék (Upper Hungary) region.
  • B. Oroszlány
    Oroszlány is a town in northwestern Hungary known historically for its coal mining and industrial character.
  • C. Balvanyos
    Balvanyos is a Romanian mountain resort area known for its natural mineral springs, spa facilities, and scenic surroundings in the Eastern Carpathians.
  • D. Nagyvázsony
    Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
  • E. Kolozsvar
    Kolozsvár is the Hungarian name for Cluj-Napoca, a major cultural, academic, and economic center in northwestern Romania and the historical capital of Transylvania.
  • 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_69d6aaff2ce88190b4a1e4b341ad5377 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a49b1080819096593733ee48a187 completed April 10, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69f77f6baca4819080f85da5fe0c2aba completed May 3, 2026, 5:01 p.m.
Created at: April 8, 2026, 9:40 p.m.