Triple

T18048801
Position Surface form Disambiguated ID Type / Status
Subject Luisito Rey E431871 entity
Predicate familyName P18 FINISHED
Object Gallego 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: Gallego | Statement: [Luisito Rey, familyName, Gallego]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gallego
Context triple: [Luisito Rey, familyName, Gallego]
  • A. Gallego chosen
    Gallego is a Spanish surname commonly associated with people of Galician origin or ancestry.
  • B. Gállego
    The Gállego is a river in northeastern Spain that flows through the Aragon region and serves as a tributary of the Ebro River.
  • C. Navarro-Aragonese
    Navarro-Aragonese is a medieval Romance language of the Iberian Peninsula, historically spoken in parts of Navarre and Aragon and known from early written records such as the Glosas Emilianenses.
  • D. Gallega
    Gallega was one of the ships in Christopher Columbus’s final transatlantic expedition, the fourth voyage undertaken to explore parts of Central and South America.
  • E. Migueleño
    Migueleño is an extinct Chumashan language once spoken by the Indigenous Chumash people in what is now Southern California.
  • 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_69d8b906482481908183315b9ecf9994 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4bff39394819080407e1614bd5da9 completed April 19, 2026, 11:43 a.m.
Created at: April 10, 2026, 10:25 a.m.