Triple
T7694306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shah Rukh Khan |
E174331
|
entity |
| Predicate | brandAmbassadorOf |
P74841
|
FINISHED |
| Object | various international and Indian brands |
—
|
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: various international and Indian brands | Statement: [Shah Rukh Khan, brandAmbassadorOf, various international and Indian brands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandAmbassadorOf Context triple: [Shah Rukh Khan, brandAmbassadorOf, various international and Indian brands]
-
A.
brandEndorsement
chosen
Indicates that one entity publicly supports, recommends, or promotes another entity’s brand, product, or service.
-
B.
fashionBrandEndorsement
Indicates a relationship where a fashion brand formally supports, promotes, or is publicly associated with an entity (such as a person, product, or event) as an endorser.
-
C.
sponsorBrandType
Indicates the type or category of brand that is acting as a sponsor in the relationship.
-
D.
sponsorAssociatedWith
Indicates a relationship where a sponsor is connected to, involved with, or responsible for supporting another entity.
-
E.
brandLaunchBy
Indicates that a particular brand was introduced or brought to market by a specific agent or organization.
- 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_69c6995966348190939e6c37ba272c06 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c706d1f0208190bc5b695aa5736244 |
completed | March 27, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69c70163dea88190ae729df50e63dfd7 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:02 p.m.