Triple

T24137952
Position Surface form Disambiguated ID Type / Status
Subject Anna Gardner E598140 entity
Predicate hasNotableProfessionalDetails P154980 FINISHED
Object not widely available 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: not widely available | Statement: [Anna Gardner, hasNotableProfessionalDetails, not widely available]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasNotableProfessionalDetails
Context triple: [Anna Gardner, hasNotableProfessionalDetails, not widely available]
  • A. hasNotableProfessionField
    Indicates that an entity’s notable profession or occupation belongs to a particular professional field or domain.
  • B. hasNotableExperience
    Indicates that an entity has a significant or distinguished experience related to another entity or context.
  • C. hasGivenProfession
    Indicates that an entity holds or practices a specified profession or occupation.
  • D. hasNotableProfessionDistributionIn
    Indicates that the distribution or prevalence of notable professions associated with an entity is observed or characterized within a specified context, such as a location or group.
  • E. hasProfessionalSection
    Indicates that an entity includes or is associated with a designated professional section, division, or category within its structure or content.
  • 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_69e288c92e448190ac57034fa0c863ce completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1df7e3c20819099ff289789829d7e completed April 29, 2026, 10:37 a.m.
PD Predicate disambiguation batch_69f1765650fc8190a6bc1eb512b240bf completed April 29, 2026, 3:09 a.m.
PDg Predicate description generation batch_69f17c28b684819084eea522126463f8 completed April 29, 2026, 3:34 a.m.
Created at: April 17, 2026, 11:27 p.m.