Triple
T2146694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mosaic 3 |
E47082
|
entity |
| Predicate | benefitScope |
P5018
|
FINISHED |
| Object | most extensive set of TrueBlue 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: most extensive set of TrueBlue benefits | Statement: [Mosaic 3, benefitScope, most extensive set of TrueBlue benefits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitScope Context triple: [Mosaic 3, benefitScope, most extensive set of TrueBlue benefits]
-
A.
hasBenefit
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
B.
benefitsState
Indicates that one entity provides an advantage, improvement, or positive outcome to a state or governmental entity.
-
C.
scopeOfUse
chosen
Indicates the range, context, or conditions under which something is intended, allowed, or applicable to be used.
-
D.
benefitsOrganizationType
Indicates that something provides an advantage, support, or positive impact specifically to a particular type or category of organization.
-
E.
sectorBenefited
Indicates that a particular sector gains advantage, support, or positive impact from a given action, policy, resource, or entity.
- 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_69a88a1933e0819094f18426ed74180f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbeaa14bc81908486683decd7ae42 |
completed | March 7, 2026, 5:59 a.m. |
| PD | Predicate disambiguation | batch_69abbd9846e88190b6c2941dd9ce7749 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:44 p.m.