Triple
T36222533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JoJo Siwa |
E1047890
|
entity |
| Predicate | hasMerchandiseLine |
P3585
|
FINISHED |
| Object | JoJo Siwa bows |
—
|
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: JoJo Siwa bows | Statement: [JoJo Siwa, hasMerchandiseLine, JoJo Siwa bows]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMerchandiseLine Context triple: [JoJo Siwa, hasMerchandiseLine, JoJo Siwa bows]
-
A.
hasClothingLine
Indicates that an entity owns, produces, or is associated with a specific line or brand of clothing.
-
B.
hasExtensiveMerchandise
Indicates that an entity offers a large and varied range of merchandise or products.
-
C.
hasProduct
chosen
Indicates that an entity possesses, offers, or is associated with a particular product.
-
D.
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.
-
E.
hasSalesComponent
Indicates that something includes, involves, or is associated with a sales-related element or function.
- 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_69f76e42c878819095c8d19c0267fb87 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff5285ed74819097e6e2a9084a079a |
completed | May 9, 2026, 3:28 p.m. |
| PD | Predicate disambiguation | batch_69ff51fbe28881908ac8417dff9db81a |
completed | May 9, 2026, 3:25 p.m. |
Created at: May 3, 2026, 4:09 p.m.