Triple
T977822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mario Kart: Koopa’s Challenge |
E21095
|
entity |
| Predicate | immersesGuestsIn |
P613
|
FINISHED |
| Object | real-life Mario Kart race |
—
|
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: real-life Mario Kart race | Statement: [Mario Kart: Koopa’s Challenge, immersesGuestsIn, real-life Mario Kart race]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: immersesGuestsIn Context triple: [Mario Kart: Koopa’s Challenge, immersesGuestsIn, real-life Mario Kart race]
-
A.
servesAtThePleasureOf
Indicates that one entity holds a position or role that can be terminated at any time by another entity, typically at the discretion or will of that other entity.
-
B.
hostsEvent
chosen
Indicates that an entity organizes and provides the venue or setting for an event to take place.
-
C.
welcomesParticipantsOf
Indicates that one entity receives or greets the participants associated with another entity in a friendly or accepting manner.
-
D.
hospitalityContext
Indicates a situational or environmental setting in which hospitality-related interactions, services, or behaviors occur.
-
E.
entersFrom
Indicates that one entity moves into or arrives at a place, state, or context by coming from another specified source or location.
- 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.