Triple
T7187660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanooki Suit |
E167610
|
entity |
| Predicate | mechanicType |
P48192
|
FINISHED |
| Object | Temporary power-up |
—
|
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: Temporary power-up | Statement: [Tanooki Suit, mechanicType, Temporary power-up]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mechanicType Context triple: [Tanooki Suit, mechanicType, Temporary power-up]
-
A.
featuresMechanic
chosen
Indicates that something includes or incorporates a particular mechanic as part of its design or functionality.
-
B.
associatedWithMechanic
Indicates a relationship where an entity is connected or linked to a mechanic, such as a process, rule, or functional mechanism involved in its operation or behavior.
-
C.
mechanicalCompatibility
Indicates that two entities can function together properly from a mechanical standpoint, without interference, damage, or performance issues.
-
D.
coachType
Indicates the specific category or role of a coach associated with an entity (e.g., head coach, assistant coach, position coach).
-
E.
isMechanicalOrElectronic
Indicates that something operates using mechanical components, electronic components, or a combination of both.
- 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_69c6888b5248819090499a884ee3ec39 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e8e2506881909fc4e81b9b79e873 |
completed | March 27, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69c6e752385c819096fbab55566ee2a8 |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:50 p.m.