Triple

T17648432
Position Surface form Disambiguated ID Type / Status
Subject Enríquez E429421 entity
Predicate regionOfPrevalence P9666 FINISHED
Object Castile 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: Castile | Statement: [Enríquez, regionOfPrevalence, Castile]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Castile
Context triple: [Enríquez, regionOfPrevalence, Castile]
  • A. Castile chosen
    Castile was a powerful medieval kingdom in central and northern Spain that became a core region of the emerging Spanish state and a major center of political, cultural, and religious influence in Iberia.
  • B. Castilla
    Castilla is a residential and commercial neighborhood in Madrid, Spain, known for its mix of modern developments and traditional urban character.
  • C. Castilla
    Castilla is a coastal municipality in the Philippine province of Sorsogon known for its agricultural lands and fishing communities.
  • D. Castilla
    Castilla is a genus of tropical American trees in the mulberry family, best known for species that produce natural rubber.
  • E. Castilla
    Castilla was a 19th-century Spanish wooden-hulled armored frigate that served in the Spanish Navy’s Pacific operations.
  • 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_69d889e2c2608190b762e76d9b2262f1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46e3bc2f8819092e3365d9e798386 completed April 19, 2026, 5:55 a.m.
Created at: April 10, 2026, 6:05 a.m.