Triple

T11460665
Position Surface form Disambiguated ID Type / Status
Subject Tzvika Brot E271649 entity
Predicate languageOfCountryOfCitizenship P99683 FINISHED
Object Hebrew 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: Hebrew | Statement: [Tzvika Brot, languageOfCountryOfCitizenship, Hebrew]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: languageOfCountryOfCitizenship
Context triple: [Tzvika Brot, languageOfCountryOfCitizenship, Hebrew]
  • A. nationalLanguageSpoken
    Indicates that a particular language is officially recognized and commonly used as a national language within a given country or region.
  • B. hasOfficialLanguageOfSurroundingCountry
    Indicates that an entity uses as its official language the same language that is official in the country surrounding it.
  • C. hasLanguageOfSurroundingCountries
    Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
  • D. hasOfficialCountryLanguage
    Indicates that a country recognizes a particular language as one of its official languages for governmental or legal purposes.
  • E. countryOfCitizenship
    Indicates the country in which a person or entity holds legal citizenship.
  • 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_69d6aadff8888190a13f253f0d460874 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d822f384f08190b1150ed1389dd31a completed April 9, 2026, 10:06 p.m.
PD Predicate disambiguation batch_69d80867ff248190bb157fa9e355353b completed April 9, 2026, 8:13 p.m.
PDg Predicate description generation batch_69d822ef46988190a1c360da4ee14fef completed April 9, 2026, 10:06 p.m.
Created at: April 8, 2026, 9:35 p.m.