Triple

T9926984
Position Surface form Disambiguated ID Type / Status
Subject Undersecretary of Agriculture of the United States E187946 entity
Predicate nativeLanguageOfWork P8513 FINISHED
Object English 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: English | Statement: [Undersecretary of Agriculture of the United States, nativeLanguageOfWork, English]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: nativeLanguageOfWork
Context triple: [Undersecretary of Agriculture of the United States, nativeLanguageOfWork, English]
  • A. nativeLanguage
    Indicates the language that a person or entity originally learned and uses as their primary or first language.
  • B. primaryLanguageOf
    Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
  • C. parentLanguage
    Indicates that one language is the ancestral or source language from which another language is derived or historically developed.
  • D. primaryLanguageSide1
    Indicates that the specified language is the main or dominant language associated with the first participant or side in a relationship.
  • E. languageOfExpression chosen
    Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
  • F. None of above.

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_69ca82b22a688190b52c75bd48429c10 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb59b85f88190899ea279fc02660f completed April 2, 2026, 12:17 a.m.
PD Predicate disambiguation batch_69cd1d90b8a8819081748f129c0c6ab6 completed April 1, 2026, 1:28 p.m.
Created at: March 30, 2026, 8:43 p.m.