Triple

T20080513
Position Surface form Disambiguated ID Type / Status
Subject Física o química E499986 entity
Predicate notableCharacter P1481 FINISHED
Object Cabano 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: Cabano | Statement: [Física o química, notableCharacter, Cabano]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cabano
Context triple: [Física o química, notableCharacter, Cabano]
  • A. Cabano chosen
    Cabano is a central teenage character from the Spanish TV series "Física o química," known for his popularity, complex relationships, and significant personal growth throughout the show.
  • B. Balbuena
    Balbuena is a metro station on Mexico City’s Line 1 serving the Balbuena neighborhood in the eastern part of the city.
  • C. Cajeme
    Cajeme is a major municipality and agricultural and industrial center in the southern part of the Mexican state of Sonora, best known for its main city Ciudad Obregón.
  • D. Bocanegra
    Bocanegra is a Spanish-origin surname borne by various notable figures, including Mexican politician and brief interim president José María Bocanegra.
  • E. Camané
    Camané is a renowned contemporary Portuguese fado singer celebrated for his expressive voice and for helping to revitalize the genre in the late 20th century.
  • 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66557c19c8190b511857490bbd423 completed April 20, 2026, 5:41 p.m.
Created at: April 11, 2026, 3:41 p.m.