Triple

T16503793
Position Surface form Disambiguated ID Type / Status
Subject Wand E400867 entity
Predicate hasMember P10 FINISHED
Object Sofia Arreguin 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: Sofia Arreguin | Statement: [Wand, hasMember, Sofia Arreguin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sofia Arreguin
Context triple: [Wand, hasMember, Sofia Arreguin]
  • A. Sofia Arreguin chosen
    Sofia Arreguin is a member of the creative collective or group known as Wand.
  • B. Sofia Huerta
    Sofia Huerta is a professional American soccer player and United States women’s national team defender known for her versatility and attacking contributions from the back line.
  • C. Ximena Lamadrid
    Ximena Lamadrid is a Mexican actress known for her work in film and television, including roles in international productions.
  • D. Selenis Leyva
    Selenis Leyva is a Cuban-American actress best known for her role as Gloria Mendoza on the Netflix series "Orange Is the New Black."
  • E. Victoria Villarruel
    Victoria Villarruel is an Argentine lawyer and politician known for her conservative stance on human rights issues and for serving as the country’s vice president alongside President Javier Milei.
  • 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_69d88381f6148190819958a038be990e completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e5100e48190a623d6ee2fefb87e completed April 18, 2026, 7:10 a.m.
Created at: April 10, 2026, 5:14 a.m.