Triple
T19306299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wrestle Kingdom |
E482836
|
entity |
| Predicate | drawingPower |
P135205
|
FINISHED |
| Object | one of the largest annual crowds in Japanese wrestling |
—
|
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: one of the largest annual crowds in Japanese wrestling | Statement: [Wrestle Kingdom, drawingPower, one of the largest annual crowds in Japanese wrestling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drawingPower Context triple: [Wrestle Kingdom, drawingPower, one of the largest annual crowds in Japanese wrestling]
-
A.
draws
Indicates that one entity creates a visual representation or image of another entity.
-
B.
drawingModel
Indicates that one entity serves as a drawing or visual representation model used to depict, design, or illustrate another entity.
-
C.
drawType
Indicates the method or style by which something is drawn, rendered, or visually represented.
-
D.
graphics
Indicates a relationship where one entity is responsible for creating, providing, or handling visual representations or graphical content for another entity or context.
-
E.
approximateNumberOfDrawings
Indicates an estimated or rough count of drawings associated with an entity.
- 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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e604c84fe08190869463bdd0324160 |
completed | April 20, 2026, 10:49 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0bc7508190a6f9d56bd4c3404f |
completed | April 19, 2026, 1:47 p.m. |
| PDg | Predicate description generation | batch_69e4ddcf50108190a09d0f1291c17374 |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 1:31 p.m.