Triple
T20350301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SA1 |
E495986
|
entity |
| Predicate | effectOnGames |
P118563
|
FINISHED |
| Object | reduces slowdown in complex scenes |
—
|
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: reduces slowdown in complex scenes | Statement: [SA1, effectOnGames, reduces slowdown in complex scenes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnGames Context triple: [SA1, effectOnGames, reduces slowdown in complex scenes]
-
A.
gameplayImpact
chosen
Indicates how one element in a game affects the mechanics, difficulty, or overall experience of playing that game.
-
B.
effectOnSystem
Indicates the influence, change, or impact that one entity, action, or condition has on the state or behavior of a system.
-
C.
effectOnUser
Indicates how an action, event, or condition influences or impacts a user.
-
D.
effectOnMachines
Indicates the influence or impact that one entity, condition, or action has on machines and their behavior or performance.
-
E.
supportsGames
Indicates that an entity is capable of running, handling, or being compatible with one or more games.
- 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_69e0b4a3320881909495ae8bc30bc2dc |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6784eacf4819095504e541d1d284d |
completed | April 20, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69e57636b4808190bc2855af48a3ccdc |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:24 a.m.