Triple

T13148476
Position Surface form Disambiguated ID Type / Status
Subject Dinosaur Land E312400 entity
Predicate hasInhabitants P6481 FINISHED
Object Luigi E11428 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 | Statement: [Dinosaur Land, hasInhabitants, Luigi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luigi
Context triple: [Dinosaur Land, hasInhabitants, Luigi]
  • A. 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.
  • B. Luigi chosen
    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 a small, enthusiastic Italian Fiat 500 who runs a tire shop and provides comic relief in Pixar's Cars franchise.
  • D. 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.
  • E. 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.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98bd0f5b08190ab700c5de1c8e138 completed April 10, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eadcd7048190aa740262679e5bab completed May 3, 2026, 6:27 a.m.
Created at: April 9, 2026, 9:11 p.m.