Triple
T15384573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Raceway |
E367884
|
entity |
| Predicate | chronologicalOrderInCup |
P23880
|
FINISHED |
| Object | third course of Star Cup in Mario Kart 64 |
—
|
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: third course of Star Cup in Mario Kart 64 | Statement: [Royal Raceway, chronologicalOrderInCup, third course of Star Cup in Mario Kart 64]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: chronologicalOrderInCup Context triple: [Royal Raceway, chronologicalOrderInCup, third course of Star Cup in Mario Kart 64]
-
A.
chronologicallyOrdered
Indicates that the related entities are arranged in the order in which they occur in time.
-
B.
chronologicalOrderInSeries
chosen
Indicates that one entity appears earlier or later than another within an ordered sequence or series.
-
C.
chronologicallyCovers
Indicates that one time period, event, or sequence extends over and includes the entire chronological span of another.
-
D.
chronologicallyClassifiedAs
Indicates that something is assigned to or placed within a specific time period or chronological category.
-
E.
chronologicalPosition
Indicates the relative ordering of one event or entity in time with respect to another.
- 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_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. |
Created at: April 10, 2026, 3:19 a.m.