Triple
T13590822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dom Pérignon |
E324686
|
entity |
| Predicate | luxurySegment |
P110196
|
FINISHED |
| Object | high-end Champagne |
—
|
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: high-end Champagne | Statement: [Dom Pérignon, luxurySegment, high-end Champagne]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: luxurySegment Context triple: [Dom Pérignon, luxurySegment, high-end Champagne]
-
A.
hasLuxuryBrands
Indicates that an entity possesses, offers, or is associated with one or more luxury brands.
-
B.
isLuxuryHotel
Indicates that a hotel is classified as a luxury establishment, typically offering high-end amenities, services, and accommodations.
-
C.
automotiveSegment
Indicates a classification relationship where an automotive product, brand, or activity is assigned to a specific market or vehicle segment within the automotive industry.
-
D.
mobilitySegment
Indicates a distinct portion or phase within a broader movement or travel activity, treated as a separate unit of mobility.
-
E.
luxMeans
Indicates that something serves as a means, method, or instrument by which a specified light-related effect, condition, or outcome is achieved.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb056ce088190a6feb4266633d18b |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae18eaf48190809e8b365856cde9 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbaf9f3bdc8190838539aaef1f422b |
completed | April 12, 2026, 2:43 p.m. |
Created at: April 9, 2026, 9:49 p.m.