Triple
T3611591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Shalhoub |
E76498
|
entity |
| Predicate | voiceRole |
P12691
|
FINISHED |
| Object | Luigi in Cars |
E236510
|
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: Luigi in Cars | Statement: [Tony Shalhoub, voiceRole, Luigi in Cars]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luigi in Cars Context triple: [Tony Shalhoub, voiceRole, Luigi in Cars]
-
A.
Peach's Kart
Peach's Kart is Princess Peach's signature pink racing vehicle featured in the Mario Kart video game series.
-
B.
Luigi
Luigi is a timid yet heroic green-clad plumber from Nintendo’s Mario franchise, known as Mario’s younger brother and frequent co-adventurer.
-
C.
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.
-
D.
Luigi
chosen
Luigi is a small, enthusiastic Italian Fiat 500 who runs a tire shop and provides comic relief in Pixar's Cars franchise.
-
E.
Lightning McQueen
Lightning McQueen is a hotshot red race car and the ambitious, charismatic protagonist of Pixar's animated Cars film series.
- 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_69ad85da0ba481908b3b48c69efe2b98 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc22e5b30819084184b730732c727 |
completed | March 8, 2026, 6:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b433136c94819099bc1d3846e54b07 |
completed | March 13, 2026, 3:53 p.m. |
Created at: March 8, 2026, 3:23 p.m.