Triple

T1168222
Position Surface form Disambiguated ID Type / Status
Subject The Hick from French Lick E24848 entity
Predicate appliedToOccupation P2374 FINISHED
Object basketball player 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: basketball player | Statement: [The Hick from French Lick, appliedToOccupation, basketball player]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: appliedToOccupation
Context triple: [The Hick from French Lick, appliedToOccupation, basketball player]
  • A. requiredOccupationOf
    Indicates that one entity specifies the occupation or job role that is required or expected for another entity (such as a position, task, or qualification).
  • B. subjectOccupation chosen
    Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
  • C. derivesFromOccupation
    Indicates that one entity originates from, is obtained through, or is a result of another entity’s occupation or professional role.
  • D. eligibleWork
    Indicates that a particular work satisfies the necessary conditions or criteria to qualify for a specified status, benefit, or consideration.
  • E. appliesToPerson
    Indicates that something (such as a rule, condition, or attribute) is relevant or applicable to a specific person.
  • 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_69a494082a7c819095004f423f294a64 completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bccef84481908864e819884af86c completed March 1, 2026, 10:25 p.m.
PD Predicate disambiguation batch_69a4bb5656948190b0b1d5446ad06005 completed March 1, 2026, 10:19 p.m.
Created at: March 1, 2026, 7:45 p.m.