Triple

T22331777
Position Surface form Disambiguated ID Type / Status
Subject Castejón E552039 entity
Predicate hasVariant P455 FINISHED
Object Castejon 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: Castejon | Statement: [Castejón, hasVariant, Castejon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Castejon
Context triple: [Castejón, hasVariant, Castejon]
  • A. Castejón chosen
    Castejón is a Spanish surname that appears as the second component in the compound family name Pérez-Castejón.
  • B. Caseres
    Caseres is a small rural municipality located in the Terra Alta comarca of Catalonia, Spain, known for its agricultural landscape and traditional village character.
  • C. Cabrils
    Cabrils is a small municipality in the Maresme comarca of Catalonia, Spain, known for its residential character and proximity to the Mediterranean coast.
  • D. Benacazón
    Benacazón is a town in the province of Seville, Spain, known for serving as an endpoint on the Seville commuter rail network.
  • E. Castelferrus
    Castelferrus is a small commune in the Tarn-et-Garonne department in southern France, situated in a rural area characterized by agriculture and proximity to the town of Castelsarrasin.
  • 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_69e11e482f788190b78d1588fc26d606 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1577b555c8190ac61c026ee7dfb2b completed April 29, 2026, 12:57 a.m.
Created at: April 16, 2026, 8:43 p.m.