Triple
T10511815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colonial Life |
E247932
|
entity |
| Predicate | employerOfferingType |
P34857
|
FINISHED |
| Object | voluntary benefits |
—
|
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: voluntary benefits | Statement: [Colonial Life, employerOfferingType, voluntary benefits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: employerOfferingType Context triple: [Colonial Life, employerOfferingType, voluntary benefits]
-
A.
employmentType
Indicates the specific kind or category of employment relationship that exists between an individual and an employer (e.g., full-time, part-time, contract).
-
B.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
-
C.
offeringType
chosen
Indicates the category or nature of what is being offered in a transaction or interaction (e.g., product, service, or other type of offering).
-
D.
offeredPosition
Indicates that one entity has extended a job or role opportunity to another entity.
-
E.
offersEnrollmentType
Indicates that an entity provides or makes available a specific type or category of enrollment option.
- 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509b5fcb8819087a23a2b26aecd70 |
completed | April 7, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69d4fb919ea08190bcc1193e2014d437 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:27 p.m.