Triple

T22713043
Position Surface form Disambiguated ID Type / Status
Subject Germans in Hungary E561651 entity
Predicate historicalRegion P915 FINISHED
Object Pest 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: Pest County | Statement: [Germans in Hungary, historicalRegion, Pest County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pest County
Context triple: [Germans in Hungary, historicalRegion, Pest County]
  • A. Pest County chosen
    Pest County is a large administrative region in central Hungary that surrounds the capital city of Budapest and serves as a major economic and transportation hub.
  • B. Mosquito County
    Mosquito County was a large early 19th-century county in territorial Florida that once encompassed much of what is now central Florida before being renamed and subdivided.
  • C. Big County
    Big County is the nickname of Perthshire, a large historic county in central Scotland known for its expansive rural landscapes and scenic beauty.
  • D. Rypin County
    Rypin County is a historical administrative district in Poland that existed within the interwar Warsaw Voivodeship.
  • E. Waradgery County
    Waradgery County is a cadastral division in New South Wales, Australia, used for land administration and property title purposes.
  • 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.