Triple
T29146208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Accuracy Shooting |
E738780
|
entity |
| Predicate | entertainmentAspect |
P120897
|
FINISHED |
| Object | showcases star players |
—
|
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: showcases star players | Statement: [Accuracy Shooting, entertainmentAspect, showcases star players]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: entertainmentAspect Context triple: [Accuracy Shooting, entertainmentAspect, showcases star players]
-
A.
entertainmentFocus
chosen
Indicates that one entity is primarily concerned with, directed toward, or centered on providing or engaging in entertainment for another entity or context.
-
B.
entertainmentType
Indicates the kind or category of entertainment associated with an entity or event.
-
C.
entertainmentRole
Indicates that an entity holds a specific function or position within an entertainment context (such as a role in a performance, production, or media work).
-
D.
inPopularCulture
Indicates that an entity is referenced, depicted, or otherwise present within works or discussions of popular culture.
-
E.
popularFilmIndustry
Indicates that an entity has a widely recognized and well-liked film industry that attracts significant audience interest and attention.
- 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_69f07cb46f148190874eb8576a447567 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69f6978fe97081908fe568091ad9b159 |
completed | May 3, 2026, 12:32 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
Created at: April 28, 2026, 11:39 a.m.