Triple

T15875706
Position Surface form Disambiguated ID Type / Status
Subject Plochingen E384947 entity
Predicate hasTwinTown P919 FINISHED
Object Oroszlány E524952 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: Oroszlány | Statement: [Plochingen, hasTwinTown, Oroszlány]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oroszlány
Context triple: [Plochingen, hasTwinTown, Oroszlány]
  • A. Oroszlány chosen
    Oroszlány is a town in northwestern Hungary known historically for its coal mining and industrial character.
  • B. Balvanyos
    Balvanyos is a Romanian mountain resort area known for its natural mineral springs, spa facilities, and scenic surroundings in the Eastern Carpathians.
  • C. Rozsnyó
    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.
  • D. Nagyvázsony
    Nagyvázsony is a village in Veszprém County, Hungary, known for its historic Kinizsi Castle and traditional rural character.
  • E. Gyor
    Győr is a historic city in northwestern Hungary, strategically located at the confluence of the Danube, Rába, and Rábca rivers and known as an important regional industrial and cultural 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_69d86da4e86481909f1325fdc971b5ec completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e155fcffbc8190ba6d133107b83a7f completed April 16, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00179d63688190bda2758ed4b4e4df completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 4:51 a.m.