Triple
T22460803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isaac Carasso |
E555223
|
entity |
| Predicate | namedBrandAfter |
P148287
|
FINISHED |
| Object | his son Daniel (Danone) |
—
|
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: his son Daniel (Danone) | Statement: [Isaac Carasso, namedBrandAfter, his son Daniel (Danone)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedBrandAfter Context triple: [Isaac Carasso, namedBrandAfter, his son Daniel (Danone)]
-
A.
formedBrand
Indicates that an entity created or established a particular brand as a distinct commercial or organizational identity.
-
B.
formerBrand
Indicates that an entity was previously used or recognized as a brand for another entity but is no longer its current brand.
-
C.
usedBrand
Indicates that an entity has utilized, applied, or operated a particular brand in some context.
-
D.
competitiveBrandName
Indicates that one brand name is in a competitive relationship with another brand name in the same market or product space.
-
E.
favoriteBrand
Indicates that one entity is the preferred or most liked brand of another entity.
- F. None of above. chosen
Provenance (4 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_69e11e51fdec8190adfdf9f8a6362221 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b7eb5688190bd5e41d4d8189668 |
completed | April 29, 2026, 1:14 a.m. |
| PD | Predicate disambiguation | batch_69e898ad961c819098fd1e46129bddcc |
completed | April 22, 2026, 9:45 a.m. |
| PDg | Predicate description generation | batch_69e8aa39e3388190b659d59948ebf3e6 |
completed | April 22, 2026, 11 a.m. |
Created at: April 16, 2026, 8:48 p.m.