Triple

T22713041
Position Surface form Disambiguated ID Type / Status
Subject Germans in Hungary E561651 entity
Predicate historicalRegion P915 FINISHED
Object Tolna County 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: Tolna County | Statement: [Germans in Hungary, historicalRegion, Tolna County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tolna County
Context triple: [Germans in Hungary, historicalRegion, 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. Zólyom County
    Zólyom County was a historic administrative county of the Kingdom of Hungary, located in what is now central Slovakia around the town of Zvolen.
  • D. 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.
  • E. Gömör-Kishont County
    Gömör-Kishont County was a historic administrative county of the Kingdom of Hungary, located in what is today southern Slovakia and northern Hungary.
  • 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_69e2454f1348819088d83f420925a5c1 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1790ab6208190a342f076002324ab completed April 29, 2026, 3:20 a.m.
Created at: April 17, 2026, 3:18 p.m.