Triple

T5854472
Position Surface form Disambiguated ID Type / Status
Subject Central Hungary E130115 entity
Predicate contains P35 FINISHED
Object Pest County E234839 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: Pest County | Statement: [Central Hungary, contains, Pest County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pest County
Context triple: [Central Hungary, contains, 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. Pest Plain
    Pest Plain is the flat, densely built-up eastern part of Budapest, known as the city’s main commercial and administrative area.
  • D. Yancowinna County
    Yancowinna County is a cadastral division in far western New South Wales, Australia, that includes the city of Broken Hill and surrounding areas.
  • E. Leting County
    Leting County is an administrative county under the jurisdiction of Tangshan City in Hebei Province, northern China, known for its coastal location along the Bohai Sea.
  • 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_69c0084de39081909eb34e6bed74215a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03554651c8190b3009d41eecf6779 completed March 22, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a1bc58d081908568294278cbf3a9 completed March 23, 2026, 2:13 a.m.
Created at: March 22, 2026, 3:55 p.m.