Triple

T18220498
Position Surface form Disambiguated ID Type / Status
Subject IYS Insurance E436288 entity
Predicate employmentStatusOfNathanFord P115041 FINISHED
Object former employee 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: former employee | Statement: [IYS Insurance, employmentStatusOfNathanFord, former employee]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: employmentStatusOfNathanFord
Context triple: [IYS Insurance, employmentStatusOfNathanFord, former employee]
  • A. employerStatus chosen
    Indicates the current employment relationship or condition between an employer and a worker, such as whether the person is actively employed, terminated, retired, or on leave.
  • B. namedForEmployer
    Indicates that an entity is named after, or in honor of, its employer.
  • C. worksAsConsultantFor
    Indicates that one entity provides professional consulting services to another entity, typically on a contractual or advisory basis.
  • D. hasFatherEmployer
    Indicates that the employer of a person’s father is related to or associated with that person.
  • E. employerInReality
    Indicates that one entity is the actual, real-world employer of another entity, as opposed to a nominal, legal, or assumed employer.
  • 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_69d8b9103a8081908bbb0836fef10efd completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4e47a3b1c8190919e954089b41ae0 completed April 19, 2026, 2:19 p.m.
PD Predicate disambiguation batch_69e4332155d88190b106d0dceb4554af completed April 19, 2026, 1:42 a.m.
Created at: April 10, 2026, 10:32 a.m.