Triple

T9703556
Position Surface form Disambiguated ID Type / Status
Subject Somogy County E234838 entity
Predicate borders P224 FINISHED
Object Tolna County E236810 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: Tolna County | Statement: [Somogy County, borders, Tolna County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tolna County
Context triple: [Somogy County, borders, Tolna County]
  • A. Tolna County chosen
    Tolna County is an administrative region in central Hungary known for its agricultural landscape and location along the Danube River.
  • 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. Fejér County
    Fejér County is an administrative region in central Hungary known for its historical significance and industrial centers, with Székesfehérvár as its county seat.
  • 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_69ca84cc78808190a56f3402b7c139a7 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9d73a0148190ad4178fd462cdd9c completed April 1, 2026, 10:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1af93b76c81908377f17956fb86b1 completed April 5, 2026, 12:40 a.m.
Created at: March 30, 2026, 8:18 p.m.