Triple
T38145444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golf le Fleur* |
E952594
|
entity |
| Predicate | brandNameFeature |
P179869
|
FINISHED |
| Object | includes an asterisk at the end |
—
|
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: includes an asterisk at the end | Statement: [Golf le Fleur*, brandNameFeature, includes an asterisk at the end]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandNameFeature Context triple: [Golf le Fleur*, brandNameFeature, includes an asterisk at the end]
-
A.
brandFeatures
chosen
Indicates that a brand includes, offers, or is characterized by a particular feature or attribute.
-
B.
brandNameType
Indicates the specific type or category associated with a brand name within a broader branding or naming system.
-
C.
brandingFeature
Indicates that one entity serves as a branding-related characteristic, element, or attribute that helps define or distinguish another entity’s brand identity.
-
D.
brandAttribute
Indicates that a specific attribute or characteristic is associated with, or describes, a particular brand.
-
E.
brandLine
Indicates that one brand is a specific product line or sub-brand offered under another brand.
- 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_69f76f09a7148190a4b91c0bacdc127a |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 3, 2026, 4:21 p.m.