Triple

T10000968
Position Surface form Disambiguated ID Type / Status
Subject Pápa E197323 entity
Predicate locatedIn P40 FINISHED
Object Veszprém County E123785 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: Veszprém County | Statement: [Pápa, locatedIn, Veszprém County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Veszprém County
Context triple: [Pápa, locatedIn, Veszprém County]
  • A. Veszprém County chosen
    Veszprém County is an administrative region in western Hungary known for its historic city of Veszprém and its location along the northern shore of Lake Balaton.
  • B. Heves County
    Heves County is an administrative region in northern Hungary known for its natural landscapes, including part of the Mátra mountain range, and historic towns such as Eger.
  • C. Pozsony County
    Pozsony County was a historic administrative region of the Kingdom of Hungary centered on the city now known as Bratislava.
  • D. Zala County
    Zala County is an administrative region in southwestern Hungary known for its rolling hills, thermal spas, and proximity to Lake Balaton and the Croatian border.
  • E. Borsod-Abaúj-Zemplén County
    Borsod-Abaúj-Zemplén County is a large administrative region in northeastern Hungary known for its industrial city of Miskolc and its diverse natural landscapes, including parts of the Bükk and Zemplén Mountains.
  • 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_69ca82f3b61c81908ecc2c1c96dbc2e4 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdcc8f50888190b2f1c5240cb58e4f completed April 2, 2026, 1:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69d979d64a5481909be6d6bd1d8b6433 completed April 10, 2026, 10:29 p.m.
Created at: March 30, 2026, 8:51 p.m.