Triple

T18331492
Position Surface form Disambiguated ID Type / Status
Subject El Llano en llamas E439151 entity
Predicate hasPart P35 FINISHED
Object Macario 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: Macario | Statement: [El Llano en llamas, hasPart, Macario]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Macario
Context triple: [El Llano en llamas, hasPart, Macario]
  • A. Macario chosen
    Macario is a classic 1960 Mexican film, directed by Roberto Gavaldón and based on a story by B. Traven, renowned for its haunting exploration of death, poverty, and fate.
  • B. Macario
    Macario is the given name of Macario Sakay, a Filipino revolutionary leader who fought against American colonial rule in the early 20th century.
  • C. Epifanio
    Epifanio is a masculine given name of Spanish origin, commonly used in Spanish-speaking countries.
  • D. Casimiro
    Casimiro is the commonly used name for Brazilian defensive midfielder Casemiro, a highly decorated footballer known for his success with Real Madrid and the Brazil national team.
  • E. Artemio
    Artemio is a masculine given name of Spanish origin, notably borne by Filipino revolutionary leader Artemio Ricarte.
  • 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_69d8b9175fec8190af865699b4e64d8c completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50eca08388190b4e757a5f63b5d41 completed April 19, 2026, 5:20 p.m.
Created at: April 10, 2026, 10:36 a.m.