Triple
T3537032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Mario |
E74795
|
entity |
| Predicate | hasSpinOff |
P7226
|
FINISHED |
| Object | Mario Golf |
E167606
|
NE 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: Mario Golf | Statement: [Super Mario, hasSpinOff, Mario Golf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mario Golf Context triple: [Super Mario, hasSpinOff, Mario Golf]
-
A.
Mario Golf
chosen
Mario Golf is a sports video game series that combines golf gameplay with characters and elements from Nintendo’s Mario franchise.
-
B.
Mario Tennis
Mario Tennis is a sports video game series by Nintendo that features Mario and other characters from the Mario franchise competing in arcade-style tennis matches.
-
C.
Golf Wang
Golf Wang is a vibrant streetwear and lifestyle brand known for its bold colors, playful graphics, and skate-inspired aesthetic.
-
D.
Hollywood Drive-In Golf
Hollywood Drive-In Golf is a themed miniature golf attraction at Universal CityWalk Orlando featuring elaborately designed, retro-style sci-fi and horror movie–inspired courses.
-
E.
Tomorrow’s Golf League
Tomorrow’s Golf League is a modern golf competition concept designed to present the sport in a more innovative, fan-friendly, and entertainment-focused format.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ad85d274cc8190ab59c97298a1cfbf |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbcc7b92481908d2d99948780f4d0 |
completed | March 8, 2026, 6:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38bd237e881909df210a42346b572 |
completed | March 13, 2026, 4 a.m. |
Created at: March 8, 2026, 3:20 p.m.