Triple

T30181508
Position Surface form Disambiguated ID Type / Status
Subject Swiss Vice-Consul in Budapest E767211 entity
Predicate hostCountryLanguageContext P169713 FINISHED
Object Hungarian LITERAL 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: Hungarian | Statement: [Swiss Vice-Consul in Budapest, hostCountryLanguageContext, Hungarian]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hostCountryLanguageContext
Context triple: [Swiss Vice-Consul in Budapest, hostCountryLanguageContext, Hungarian]
  • A. languageOfSurroundingCountry
    Indicates that a language is the primary or commonly used language in the country surrounding a given place or region.
  • B. countryOfLanguage
    Indicates that a particular language is officially or predominantly used within a specified country.
  • C. primaryLanguageCountry
    Indicates that a given language is the main or officially predominant language used within a particular country.
  • D. governingCountryLanguage
    Indicates that a particular language is officially used or recognized by the governing authorities of a given country.
  • E. nativeLanguageContext
    Indicates the relationship in which a language functions as the primary or native linguistic context for an entity’s communication or interpretation.
  • F. None of above. chosen

Provenance (4 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_69f2247cc3d88190811dec3face94bf5 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68048391c8190abe6580678f8a9ef completed May 2, 2026, 10:52 p.m.
PD Predicate disambiguation batch_69f67e40af9881908de3a4aa15f70a83 completed May 2, 2026, 10:44 p.m.
PDg Predicate description generation batch_69f67f7e116c819099aec724e9ef3763 completed May 2, 2026, 10:49 p.m.
Created at: April 29, 2026, 7:26 p.m.