Triple

T22730677
Position Surface form Disambiguated ID Type / Status
Subject Atchison, Topeka and Santa Fe Railway E562125 entity
Predicate shortName P43 FINISHED
Object Santa Fe 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: Santa Fe | Statement: [Atchison, Topeka and Santa Fe Railway, shortName, Santa Fe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Fe
Context triple: [Atchison, Topeka and Santa Fe Railway, shortName, Santa Fe]
  • A. Santa Fe
    Santa Fe is a barangay (village-level administrative division) located in the municipality of San Felipe in the province of Zambales, Philippines.
  • B. Santa Fe
    Santa Fe is a historic town in Spain’s Granada province, known as the place where the Catholic Monarchs completed the Reconquista and agreed to sponsor Christopher Columbus’s voyage.
  • C. Santa Fe
    Santa Fe is a town on Cuba’s Isla de la Juventud, known as one of the island’s principal local settlements.
  • D. Santa Fe chosen
    Santa Fe is the capital city of New Mexico, known for its Pueblo-style architecture, vibrant arts scene, and rich blend of Native American and Spanish colonial history.
  • E. Santa Fe
    Santa Fe is a major modern business and financial district in western Mexico City known for its corporate offices, upscale shopping centers, and contemporary high-rise architecture.
  • 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_69e24550859c81908727d91efc3a81b4 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1792cb9cc8190a7c45032427bca1a completed April 29, 2026, 3:21 a.m.
Created at: April 17, 2026, 3:21 p.m.