Triple

T14212737
Position Surface form Disambiguated ID Type / Status
Subject Ancient Iberia E352270 entity
Predicate includes P1393 FINISHED
Object Vasconia E73512 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: Vasconia | Statement: [Ancient Iberia, includes, Vasconia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vasconia
Context triple: [Ancient Iberia, includes, Vasconia]
  • A. Tasqueña
    Tasqueña is a major transit hub and southern terminus of Mexico City’s Metro Line 2, integrating metro, light rail, and bus services.
  • B. Vizcaya
    Vizcaya was a Spanish armored cruiser of the late 19th century that served in the Spanish–American War as part of the Spanish Caribbean Squadron.
  • C. Landes
    Landes is a department in southwestern France known for its vast Atlantic coastline, extensive pine forests, and popular surfing beaches.
  • D. Navarre chosen
    Navarre is an autonomous community and historical region in northern Spain known for its diverse landscapes, rich cultural traditions, and capital city of Pamplona.
  • E. Navarre
    Navarre is a coastal community in northwest Florida known for its white-sand beaches and family-friendly atmosphere along the Gulf of Mexico.
  • 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_69d8278a06e481908b5d6af0a8afe737 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de620dba0c8190bb77a1df10e1d3a7 completed April 14, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd19574280819091bafd95a75983bf completed May 7, 2026, 10:59 p.m.
Created at: April 10, 2026, 1:05 a.m.