Triple

T10345048
Position Surface form Disambiguated ID Type / Status
Subject Sal Velez Jr. E243722 entity
Predicate hasFamilyName P18 FINISHED
Object Velez E177187 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: Velez | Statement: [Sal Velez Jr., hasFamilyName, Velez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Velez
Context triple: [Sal Velez Jr., hasFamilyName, Velez]
  • A. Vélez chosen
    Vélez is a Spanish-language surname common in Latin America and Spain, borne by various notable figures in arts, sports, and public life.
  • B. Vélez
    Vélez is a municipality in Colombia’s Santander Department known for its colonial heritage and traditional sweets.
  • C. Curaco de Vélez
    Curaco de Vélez is a small coastal town and commune in southern Chile’s Chiloé Archipelago, known for its traditional Chilote culture and wooden architecture.
  • D. Quintero
    Quintero is a coastal Chilean city known for its beaches, port activities, and role as part of the Valparaíso Region’s industrial and tourism corridor.
  • E. Varela
    Varela is a Spanish surname borne by numerous notable figures in politics, the military, arts, and public life across the Spanish-speaking world.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9228cd88190bcd94b85537233c1 completed April 7, 2026, 11:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7507f708c8190b8cf684704a6e47d completed April 9, 2026, 7:08 a.m.
Created at: April 6, 2026, 11:56 a.m.