Triple
T29095260
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panther blue jersey |
E734978
|
entity |
| Predicate | fanMerchandiseAvailable |
P166310
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Panther blue jersey, fanMerchandiseAvailable, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fanMerchandiseAvailable Context triple: [Panther blue jersey, fanMerchandiseAvailable, yes]
-
A.
merchandiseSource
Indicates that one entity is the origin, supplier, or provider from which another entity’s merchandise is obtained.
-
B.
usedInMerchandise
Indicates that something (such as a work, character, or design) is utilized or featured as part of a merchandise item.
-
C.
hasMerchandiseTieIn
Indicates that one entity has a commercial or promotional product or line (merchandise) that is directly tied to, branded with, or derived from another entity.
-
D.
hasFictionalProduct
Indicates a relationship where one entity features, offers, or includes a product that exists only in fiction or an imagined context.
-
E.
isCollectibleFigure
Indicates that an entity is a figure or model intended primarily for collection rather than ordinary use or play.
- 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_69f05b0ed66481908f2e864fa550d2f1 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f6618069888190aa87dd09a751a2c2 |
completed | May 2, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f65c2376a08190be5215171e908e69 |
completed | May 2, 2026, 8:18 p.m. |
| PDg | Predicate description generation | batch_69f65f75ac608190a62cd6afce14f68e |
completed | May 2, 2026, 8:32 p.m. |
Created at: April 28, 2026, 11:08 a.m.