Triple

T9685767
Position Surface form Disambiguated ID Type / Status
Subject Zagyva E234402 entity
Predicate flowsThroughCounty P4247 FINISHED
Object Nógrád County E338312 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: Nógrád County | Statement: [Zagyva, flowsThroughCounty, Nógrád County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nógrád County
Context triple: [Zagyva, flowsThroughCounty, Nógrád County]
  • A. Nógrád County chosen
    Nógrád County is a northern Hungarian administrative region known for its hilly landscapes, historic towns, and portions of the Mátra and Cserhát mountain ranges.
  • B. Somogy County
    Somogy County is an administrative region in southwestern Hungary, known for its rural landscapes and proximity to Lake Balaton.
  • C. Tolna County
    Tolna County is an administrative region in central Hungary known for its agricultural landscape and location along the Danube River.
  • 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_69ca84ca73208190957a900c8543bdcc completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9cd2dab481908e0d3fed28de9d40 completed April 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1910b7c148190b9061b1ce0520e8b completed April 4, 2026, 10:30 p.m.
Created at: March 30, 2026, 8:16 p.m.