Triple
T33941531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Memorial Day Miracle |
E870178
|
entity |
| Predicate | hasShotType |
P30535
|
FINISHED |
| Object | three-pointer |
—
|
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: three-pointer | Statement: [Memorial Day Miracle, hasShotType, three-pointer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasShotType Context triple: [Memorial Day Miracle, hasShotType, three-pointer]
-
A.
shotType
chosen
Indicates the specific kind or category of shot used or taken in a given context (e.g., in film, photography, or sports).
-
B.
hasShootingPosition
Indicates that an entity has a designated location or spot from which shooting (e.g., firing a weapon or taking a shot) is performed.
-
C.
madeShot
Indicates that an entity successfully completed a shot attempt, such as scoring in a game or sport.
-
D.
shotOn
Indicates that one entity fired or took a shot at another entity, typically in a sports or combat context.
-
E.
hasWeaponType
Indicates that an entity is associated with or equipped with a specific type or category of weapon.
- 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_69f3499b0dd48190b07b4b60babcee02 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f78fd5a6388190bfda4bbb2e222e5b |
completed | May 3, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69f78e2ac3fc819081a45c6841375c8d |
completed | May 3, 2026, 6:04 p.m. |
Created at: May 1, 2026, 1:49 a.m.