Triple

T4122534
Position Surface form Disambiguated ID Type / Status
Subject Cebu Island E92646 entity
Predicate hasMunicipality P847 FINISHED
Object Santa Fe E289439 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: [Cebu Island, hasMunicipality, Santa Fe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Fe
Context triple: [Cebu Island, hasMunicipality, 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
    Santa Fe is a historic Argentine city and provincial capital known for its colonial heritage and strategic location on the Paraná River.
  • D. Santa Fe chosen
    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, New Mexico
    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.
  • 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_69aed9685f70819086932777aec8d959 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69af020728a08190a50a16b40690cbce completed March 9, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf856d4d6481908b99610cf52abc76 completed March 22, 2026, 6 a.m.
Created at: March 9, 2026, 3:41 p.m.