Triple
T464729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roy Rogers |
E8418
|
entity |
| Predicate | hasMerchandise |
P3585
|
FINISHED |
| Object | Roy Rogers lunchboxes |
—
|
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: Roy Rogers lunchboxes | Statement: [Roy Rogers, hasMerchandise, Roy Rogers lunchboxes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMerchandise Context triple: [Roy Rogers, hasMerchandise, Roy Rogers lunchboxes]
-
A.
hasProduct
chosen
Indicates that an entity possesses, offers, or is associated with a particular product.
-
B.
hasCulturalProduct
Indicates that an entity possesses, produces, or is associated with a cultural artifact, work, or output (such as art, literature, music, or media).
-
C.
hasTrade
Indicates a relationship where one entity engages in or maintains a commercial exchange or trading activity with another entity.
-
D.
hasMarketingCategory
Indicates that an entity is associated with a specific marketing category or segment used for classification or targeting.
-
E.
canBePurchasedWith
Indicates that one entity is able to be bought or acquired using another entity as the form of payment.
- 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_69a2e7f3aeb48190a19453e3a043f486 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efd5b6b48190ae23968135cf6417 |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2edea1acc81908a72d9f4c43438ea |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.