Triple

T26745277
Position Surface form Disambiguated ID Type / Status
Subject Martha Sandoval E674380 entity
Predicate languageRelatedIssue P189705 FINISHED
Object access to driver’s license test for non-English speakers 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: access to driver’s license test for non-English speakers | Statement: [Martha Sandoval, languageRelatedIssue, access to driver’s license test for non-English speakers]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: languageRelatedIssue
Context triple: [Martha Sandoval, languageRelatedIssue, access to driver’s license test for non-English speakers]
  • A. languageOfIssue
    Indicates the language in which a particular item, document, or resource is issued or published.
  • B. languageAffected
    Indicates that one entity has an impact on, modifies, or influences the characteristics, usage, or status of a language.
  • C. languageIndependence
    Indicates that a concept, method, or representation does not depend on any specific programming or natural language and can be applied uniformly across different languages.
  • D. languageConsultant
    Indicates that one entity serves as a language consultant, providing expert advice or guidance on language-related matters to another entity.
  • E. languageSubject
    Indicates that a particular language is the subject or topic being studied, discussed, or otherwise focused on in relation to another entity.
  • 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_69eecda63a3881908095c47900692e65 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69fbca6c066c8190a1599202f341417f completed May 6, 2026, 11:10 p.m.
PD Predicate disambiguation batch_69fbc8ec03ac8190a757563f96fab283 completed May 6, 2026, 11:04 p.m.
PDg Predicate description generation batch_69fbc9d0854c8190aa00093274afebb8 completed May 6, 2026, 11:08 p.m.
Created at: April 27, 2026, 3:51 a.m.