Triple

T5977105
Position Surface form Disambiguated ID Type / Status
Subject Mário de Andrade E133025 entity
Predicate givenName P17 FINISHED
Object Mário E529899 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: Mário | Statement: [Mário de Andrade, givenName, Mário]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mário
Context triple: [Mário de Andrade, givenName, Mário]
  • A. Mário chosen
    Mário is a masculine given name of Latin origin, widely used in Portuguese- and Italian-speaking countries.
  • B. Mario
    Mario is an American R&B singer, songwriter, and occasional actor best known for his early-2000s hits like "Let Me Love You."
  • C. Mario
    Mario is a fictional Italian plumber and the iconic protagonist of Nintendo's long-running Super Mario video game franchise.
  • D. 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.
  • E. 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.
  • 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_69c0086f45e8819098f73dd16d45ec9d completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04a3cffb08190a764a404a4ce5812 completed March 22, 2026, 7:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e4184a708190a9e4fe8453463a4b completed March 23, 2026, 6:56 a.m.
Created at: March 22, 2026, 4:04 p.m.