Triple

T1587319
Position Surface form Disambiguated ID Type / Status
Subject New Mexico E34095 entity
Predicate hasCity P316 FINISHED
Object Santa Fe 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 | Statement: [New Mexico, hasCity, Santa Fe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Fe
Context triple: [New Mexico, hasCity, Santa Fe]
  • A. Santa Fe
    Santa Fe is a town on Cuba’s Isla de la Juventud, known as one of the island’s principal local settlements.
  • B. 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.
  • C. 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.
  • D. Albuquerque
    Albuquerque is the largest city in New Mexico, known for its high desert landscape, multicultural heritage, and institutions like the University of New Mexico.
  • E. San Luis
    San Luis is a residential and commercial district located in the eastern part of Lima, Peru.
  • 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_69a885fceb2c8190b47e0f7c0aefbff0 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a9090b3a20819098fdb5605ee739d7 completed March 5, 2026, 4:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5d78933c81908359b0010b9e6147 completed March 9, 2026, 5:41 a.m.
Created at: March 4, 2026, 7:27 p.m.