Triple

T538071
Position Surface form Disambiguated ID Type / Status
Subject Joe Buck E12369 entity
Predicate hasOccupationSpecialization P466 FINISHED
Object baseball play-by-play 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: baseball play-by-play | Statement: [Joe Buck, hasOccupationSpecialization, baseball play-by-play]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasOccupationSpecialization
Context triple: [Joe Buck, hasOccupationSpecialization, baseball play-by-play]
  • A. hasSpecialty chosen
    Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
  • B. derivesFromOccupation
    Indicates that one entity originates from, is obtained through, or is a result of another entity’s occupation or professional role.
  • C. subjectOccupation
    Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
  • D. hasNotableBearerOccupation
    Indicates that an entity is associated with a notable person who holds a specific occupation.
  • E. 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.
  • 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_69a4933208e88190891f5debab1b776d completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4985e51908190a34aa82ea9dbee1e completed March 1, 2026, 7:49 p.m.
PD Predicate disambiguation batch_69a494b51ff08190a39f4168fd9a7ddf completed March 1, 2026, 7:34 p.m.
Created at: March 1, 2026, 7:32 p.m.