Triple
T15384847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Shell |
E367890
|
entity |
| Predicate | gameplayImpact |
P118563
|
FINISHED |
| Object | increases unpredictability of race results |
—
|
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 unpredictability of race results | Statement: [Blue Shell, gameplayImpact, increases unpredictability of race results]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gameplayImpact Context triple: [Blue Shell, gameplayImpact, increases unpredictability of race results]
-
A.
impactOnField
Indicates the effect or influence that one entity, action, or development has on a particular field or domain.
-
B.
gameplayMechanic
Indicates a relationship where one entity functions as a rule, system, or interactive feature that defines how another entity can be played or operated within a game.
-
C.
impactOnStandings
Indicates how an event or outcome affects the relative rankings or standings within a competition or system.
-
D.
scoreEffect
Indicates the impact or change that an action, event, or condition has on a score or scoring outcome.
-
E.
gameModeRelevance
Indicates how strongly or in what way something is related or applicable to a particular game mode.
- F. None of above. chosen
Provenance (4 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e7397188190bde42b897ab4b5b4 |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27742a881909cd73cc5c7d062fd |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded57005608190886cd01f640dfedb |
completed | April 15, 2026, 12:01 a.m. |
Created at: April 10, 2026, 3:19 a.m.