Triple

T5402423
Position Surface form Disambiguated ID Type / Status
Subject Komárom-Esztergom County E120808 entity
Predicate countrySubdivisionOf P766 FINISHED
Object Hungary E5017 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: Hungary | Statement: [Komárom-Esztergom County, countrySubdivisionOf, Hungary]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hungary
Context triple: [Komárom-Esztergom County, countrySubdivisionOf, Hungary]
  • A. Hungary chosen
    Hungary is a landlocked Central European country known for its rich history, distinct language (Hungarian), and capital city Budapest, famed for its thermal baths and architecture.
  • B. Ungar
    Ungar is a surname of Germanic and Central European origin, historically associated with people from Hungary or of Hungarian descent.
  • C. Slovakia and Hungary
    Slovakia and Hungary are neighboring Central European countries that share a significant stretch of their border along the Danube River.
  • D. Austria
    Austria is a landlocked Central European country known for its Alpine landscapes, rich cultural and musical heritage, and status as a prosperous, democratic member of the European Union.
  • E. Slovakia
    Slovakia is a landlocked Central European country known for its mountainous landscapes, medieval castles, and membership in major international organizations such as the European Union and NATO.
  • 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_69bd46391c0c81909fa484446732b6a3 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd87731c1c81909a4dc865282bd289 completed March 20, 2026, 5:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf3388c10481908235da34ef509d37 completed March 22, 2026, 12:10 a.m.
Created at: March 20, 2026, 2:04 p.m.