Triple

T10182063
Position Surface form Disambiguated ID Type / Status
Subject Tolna County E236810 entity
Predicate bordersCounty P6346 FINISHED
Object Fejér County E32753 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: Fejér County | Statement: [Tolna County, bordersCounty, Fejér County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fejér County
Context triple: [Tolna County, bordersCounty, Fejér County]
  • A. Fejér County chosen
    Fejér County is an administrative region in central Hungary known for its historical significance and industrial centers, with Székesfehérvár as its county seat.
  • B. Somogy County
    Somogy County is an administrative region in southwestern Hungary, known for its rural landscapes and proximity to Lake Balaton.
  • C. Nógrád County
    Nógrád County is a northern Hungarian administrative region known for its hilly landscapes, historic towns, and portions of the Mátra and Cserhát mountain ranges.
  • D. Tolna County
    Tolna County is an administrative region in central Hungary known for its agricultural landscape and location along the Danube River.
  • E. Liptó County
    Liptó County was a historic administrative county of the Kingdom of Hungary, located in the northern part of present-day Slovakia and centered around the Liptov 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_69ca84d7260c8190bfbec36762943f37 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cded32b91c8190b01ad37b2456080a completed April 2, 2026, 4:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69d8dbe24a64819098bc94a8a62cc46b completed April 10, 2026, 11:15 a.m.
Created at: March 30, 2026, 9:12 p.m.