Triple

T14582809
Position Surface form Disambiguated ID Type / Status
Subject Argentaria E342235 entity
Predicate predecessorOf P97 FINISHED
Object BBVA E66584 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: BBVA | Statement: [Argentaria, predecessorOf, BBVA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BBVA
Context triple: [Argentaria, predecessorOf, BBVA]
  • A. BBVA USA
    BBVA USA was a U.S.-based banking institution offering retail and commercial financial services as part of the global BBVA Group.
  • B. Banco Santander
    Banco Santander is a major global Spanish banking group offering retail and commercial financial services across Europe, the Americas, and other international markets.
  • C. Banco Bilbao Vizcaya Argentaria chosen
    Banco Bilbao Vizcaya Argentaria (BBVA) is a major multinational Spanish banking group that provides a wide range of financial services across Europe, the Americas, and other global markets.
  • D. Banamex
    Banamex is one of Mexico’s largest and oldest banking institutions, offering a wide range of financial services to retail and corporate customers.
  • E. Banesto
    Banesto was a prominent Spanish professional cycling team, sponsored by the Banco Español de Crédito, best known for supporting Miguel Indurain during his multiple Tour de France victories in the early 1990s.
  • 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_69d822ddc0f081909cd8163c7de298cd completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb41e71748190a1deacc819dd26d3 completed April 14, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fda9167b888190abb8f301b0c7c55b completed May 8, 2026, 9:12 a.m.
Created at: April 10, 2026, 1:24 a.m.