Triple
T21751927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gingembre Rouge |
E536934
|
entity |
| Predicate | hasKeyBenefitClaim |
P2188
|
FINISHED |
| Object | invigorating sensation |
—
|
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: invigorating sensation | Statement: [Gingembre Rouge, hasKeyBenefitClaim, invigorating sensation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKeyBenefitClaim Context triple: [Gingembre Rouge, hasKeyBenefitClaim, invigorating sensation]
-
A.
hasBenefit
chosen
Indicates that one entity provides an advantage, improvement, or positive outcome to another entity.
-
B.
hasBenefitType
Indicates that an entity is associated with a specific category or type of benefit it provides or receives.
-
C.
benefitAppliesTo
Indicates that a particular benefit is applicable to, or valid for, a specified entity or context.
-
D.
isIndividualBenefit
Indicates that something provides a benefit or advantage to a single individual rather than to a group or collective.
-
E.
hasDifferentBenefitsThan
Indicates that the benefits provided by one entity are not the same as those provided by another 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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01d8a6d4881908cc69e7247cce3a5 |
completed | April 28, 2026, 2:38 a.m. |
| PD | Predicate disambiguation | batch_69e6969c16fc8190b5126c169317d85d |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:50 p.m.