Triple
T13639168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sikma move |
E325929
|
entity |
| Predicate | typicalShotType |
P30535
|
FINISHED |
| Object | face-up jumper |
—
|
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: face-up jumper | Statement: [Sikma move, typicalShotType, face-up jumper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalShotType Context triple: [Sikma move, typicalShotType, face-up jumper]
-
A.
typicalStillType
Indicates that something represents the usual or characteristic form, style, or configuration that an entity typically has or uses.
-
B.
shotType
chosen
Indicates the specific kind or category of shot used or taken in a given context (e.g., in film, photography, or sports).
-
C.
shotOn
Indicates that one entity fired or took a shot at another entity, typically in a sports or combat context.
-
D.
typeOfStills
Indicates that one entity is a specific kind or category of stills (e.g., a particular type or style within the broader class of still images or still photography).
-
E.
shootingStyle
Indicates the characteristic manner or technique with which an entity performs a shooting action (e.g., in sports or photography).
- 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_69d8076beddc8190a53156f5bea77f5e |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc60635d08190899806fe8936f02a |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe85e1c4819095194f4b7f9f6118 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:51 p.m.