Triple
T26729554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokyo Racecourse |
E673927
|
entity |
| Predicate | videoScreenType |
P139272
|
FINISHED |
| Object | large outdoor screen |
—
|
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: large outdoor screen | Statement: [Tokyo Racecourse, videoScreenType, large outdoor screen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: videoScreenType Context triple: [Tokyo Racecourse, videoScreenType, large outdoor screen]
-
A.
videoType
Indicates the classification or category of a video (such as format, genre, or purpose) associated with an entity.
-
B.
visualDevice
Indicates a relationship where an entity functions as or is associated with a device used for visual display, capture, or processing.
-
C.
screenCategory
chosen
Indicates the classification or type of screen associated with an entity (e.g., by function, layout, or usage context).
-
D.
videoOutput
Indicates that one entity produces or provides video signals or content as output to another entity or medium.
-
E.
videoPlatform
Indicates a relationship where an entity serves as or is associated with a platform used for hosting, sharing, or streaming video content.
- 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_69eecda57ab481909424e98f2835e7d8 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f618401d2481908b10199b30333192 |
completed | May 2, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69f60b8dfa0c8190864e1a940024d0a0 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 27, 2026, 3:44 a.m.