Triple

T18834824
Position Surface form Disambiguated ID Type / Status
Subject Kimo Leopoldo E460633 entity
Predicate name P16 FINISHED
Object Kimo Leopoldo NE NERFINISHED

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: Kimo Leopoldo | Statement: [Kimo Leopoldo, name, Kimo Leopoldo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kimo Leopoldo
Context triple: [Kimo Leopoldo, name, Kimo Leopoldo]
  • A. Kimo Leopoldo chosen
    Kimo Leopoldo is an American former mixed martial artist and kickboxer who gained prominence in the early days of the UFC.
  • B. Filiberto
    Filiberto was a Puerto Rican nationalist and militant leader associated with the Puerto Rican independence movement.
  • C. Teodoro
    Teodoro is a given name, commonly used in Romance-language countries, that corresponds to the English name Theodore.
  • D. Hipólito Unanue
    Hipólito Unanue was a prominent Peruvian physician, scientist, and statesman of the late colonial and early republican periods, noted for his contributions to medicine, enlightenment thought, and the political formation of independent Peru.
  • E. Udenio
    Udenio is an Italian surname most notably associated with actress Fabiana Udenio, known for her work in film and television.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dcf94c288190a06dea029ae4b223 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5a99c1394819095c62eef040e552c completed April 20, 2026, 4:20 a.m.
Created at: April 10, 2026, 11:56 a.m.