Triple

T11744664
Position Surface form Disambiguated ID Type / Status
Subject U.S. Route 285 E279246 entity
Predicate passesThrough P225 FINISHED
Object Santa Fe, New Mexico E8570 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: Santa Fe, New Mexico | Statement: [U.S. Route 285, passesThrough, Santa Fe, New Mexico]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Fe, New Mexico
Context triple: [U.S. Route 285, passesThrough, Santa Fe, New Mexico]
  • A. Santa Fe, New Mexico chosen
    Santa Fe, New Mexico is the capital city of New Mexico, renowned for its Pueblo-style architecture, vibrant arts scene, and rich blend of Native American, Hispanic, and Anglo cultures.
  • B. Santa Fe
    Santa Fe is a town on Cuba’s Isla de la Juventud, known as one of the island’s principal local settlements.
  • C. 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.
  • D. Santa Fe
    Santa Fe is a coastal municipality on Bantayan Island in Cebu, Philippines, known for its white-sand beaches and laid-back island atmosphere.
  • E. Santa Fe
    Santa Fe was a major American railroad company that played a key role in the development and transportation infrastructure of the western United States.
  • 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_69d6ab01038c819080714901502c84fc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4f2a38c8190a682d8dae1ab9415 completed April 10, 2026, 7:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69f4174972ac819094f3938b18a5081e completed May 1, 2026, 3 a.m.
Created at: April 8, 2026, 9:41 p.m.