Triple
T977808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mario Kart: Koopa’s Challenge |
E21095
|
entity |
| Predicate | hasInteractiveElement |
P3970
|
FINISHED |
| Object | steering simulation |
—
|
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: steering simulation | Statement: [Mario Kart: Koopa’s Challenge, hasInteractiveElement, steering simulation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInteractiveElement Context triple: [Mario Kart: Koopa’s Challenge, hasInteractiveElement, steering simulation]
-
A.
hasInteraction
chosen
Indicates that there is some form of interaction or mutual action occurring between the related entities.
-
B.
hasIconicElement
Indicates that something contains or features a distinctive, widely recognized element that symbolizes its identity or significance.
-
C.
hasPrimaryFocus
Indicates that something is the main subject, concern, or area of attention for an entity or activity.
-
D.
hasMouse
Indicates that an entity possesses, uses, or is associated with a mouse (typically a computer pointing device or a small rodent).
-
E.
hasCurrent
Indicates that an entity presently possesses, exhibits, or is associated with a particular state, attribute, or resource at the current time.
- 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_69a493c2b62c8190b616351789ec47f8 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b47861808190be56a7bbd926e658 |
completed | March 1, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a8a3b08190b4538e119b13f7f5 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:40 p.m.