Triple
T4135934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanity Fair |
E85154
|
entity |
| Predicate | productTypeVariant |
P455
|
FINISHED |
| Object | luncheon napkins |
—
|
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: luncheon napkins | Statement: [Vanity Fair, productTypeVariant, luncheon napkins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: productTypeVariant Context triple: [Vanity Fair, productTypeVariant, luncheon napkins]
-
A.
brandNameVariant
Indicates that one brand name is an alternative or variant form of another brand name, such as a spelling, regional, or stylistic variation.
-
B.
designVariant
Indicates that one entity is an alternative design or version derived from or related to another entity’s design.
-
C.
hasVariant
chosen
Indicates that one entity exists as an alternative form, version, or variation of another entity.
-
D.
primaryVariant
Indicates that one entity is the main or canonical version among multiple related variants of another entity.
-
E.
productStyle
Indicates the stylistic category or design theme that characterizes a product.
- 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_69aed935ccd881909dc61f81bcdb7a78 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af018a54848190987f18c066c75068 |
completed | March 9, 2026, 5:21 p.m. |
Created at: March 9, 2026, 3:43 p.m.