Triple
T15558384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waluigi Stadium |
E370929
|
entity |
| Predicate | themedAfter |
P5290
|
FINISHED |
| Object | Waluigi |
E368633
|
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: Waluigi | Statement: [Waluigi Stadium, themedAfter, Waluigi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waluigi Context triple: [Waluigi Stadium, themedAfter, Waluigi]
-
A.
Waluigi
chosen
Waluigi is a lanky, mustachioed antagonist from Nintendo’s Mario franchise, often appearing as Wario’s partner in spin-off sports and party games.
-
B.
Wario
Wario is a greedy, mischievous antihero in Nintendo’s Mario franchise, known for his brutish strength, distinctive yellow and purple outfit, and starring role in the Wario Land and WarioWare game series.
-
C.
Luigi
Luigi is a small, enthusiastic Italian Fiat 500 who runs a tire shop and provides comic relief in Pixar's Cars franchise.
-
D.
Luigi
Luigi is the birth name of Hall of Fame basketball coach Geno Auriemma, renowned for leading the University of Connecticut women's team to multiple national championships.
-
E.
Luigi
Luigi is a character in Robert Browning's verse drama "Pippa Passes," depicted as an Italian patriot involved in a plot against Austrian rule.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04dda3ab88190ab383333ce69fe8f |
completed | April 16, 2026, 2:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff4c4046c08190a43bd5577a97f33d |
completed | May 9, 2026, 3:01 p.m. |
Created at: April 10, 2026, 4:09 a.m.