Triple
T7187419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mario Tennis |
E167605
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object | Wario |
E169883
|
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: Wario | Statement: [Mario Tennis, featuresCharacter, Wario]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wario Context triple: [Mario Tennis, featuresCharacter, Wario]
-
A.
Wario
chosen
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.
-
B.
Waluigi
Waluigi is a lanky, mustachioed antagonist from Nintendo’s Mario franchise, often appearing as Wario’s partner in spin-off sports and party games.
-
C.
Yoshi
Yoshi is a friendly, dinosaur-like character from Nintendo’s Mario franchise, known for his long tongue, egg-throwing abilities, and frequent role as Mario’s companion and steed.
-
D.
Kamek
Kamek is a recurring Magikoopa villain in the Mario franchise, typically depicted as Bowser’s magical advisor and caretaker who uses powerful spells to hinder Mario and his allies.
-
E.
Mário
Mário is a masculine given name of Latin origin, widely used in Portuguese- and Italian-speaking countries.
- 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_69c6888b5248819090499a884ee3ec39 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e8e2506881909fc4e81b9b79e873 |
completed | March 27, 2026, 8:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7cbe39e6881909d65aa44ba4273a1 |
completed | March 28, 2026, 12:38 p.m. |
Created at: March 27, 2026, 2:50 p.m.