Triple

T21692304
Position Surface form Disambiguated ID Type / Status
Subject Bihor County E535400 entity
Predicate locatedIn P40 FINISHED
Object Crișana NE NERFINISHED

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: Crișana | Statement: [Bihor County, locatedIn, Crișana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Crișana
Context triple: [Bihor County, locatedIn, Crișana]
  • A. Crișana chosen
    Crișana is a historical region in western Romania, known for its multicultural heritage and location between the Apuseni Mountains and the Hungarian border.
  • B. Argeș
    Argeș is a county in southern Romania known for its historical significance, including Curtea de Argeș Monastery and parts of the Carpathian Mountains.
  • C. Satu Mare
    Satu Mare is a city in northwestern Romania near the Hungarian border, known as a regional economic and cultural center with a diverse ethnic heritage.
  • D. Piatra-Olt
    Piatra-Olt is a small town in southern Romania known as a local railway junction and administrative center within Olt County.
  • E. Caransebeș
    Caransebeș is a historic town in western Romania, situated in the Banat region and known as an important local cultural and transportation hub.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c46a6ee481908836e1420fb78c9b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef96d0d4048190abfc3e3e06c51b8d completed April 27, 2026, 5:03 p.m.
Created at: April 16, 2026, 6:45 p.m.