Triple
T38477253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wumpa Fruit |
E915579
|
entity |
| Predicate | effectInRacingGames |
P118563
|
FINISHED |
| Object | Increases speed or stats when enough are collected |
—
|
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: Increases speed or stats when enough are collected | Statement: [Wumpa Fruit, effectInRacingGames, Increases speed or stats when enough are collected]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectInRacingGames Context triple: [Wumpa Fruit, effectInRacingGames, Increases speed or stats when enough are collected]
-
A.
effectOnDrivingStyle
Indicates how one factor or condition influences or alters a person's manner or style of driving.
-
B.
inMarioKartEffect
Indicates that one entity is currently under the influence of another entity’s effect within the context of Mario Kart gameplay.
-
C.
gameplayImpact
chosen
Indicates how one element in a game affects the mechanics, difficulty, or overall experience of playing that game.
-
D.
fuelEffect
Indicates the influence or impact that a given fuel has on a process, system, or outcome.
-
E.
featuresRaceBetween
Indicates that an event or context includes or showcases a competitive race occurring between participants.
- 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_69f76e8ff5cc8190a88803369183845e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe629b4fa481908467c7c41b77f0c6 |
completed | May 8, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69fe61bb260c819083f9378a3a06ca47 |
completed | May 8, 2026, 10:20 p.m. |
Created at: May 3, 2026, 4:31 p.m.