Triple

T5153326
Position Surface form Disambiguated ID Type / Status
Subject Bantayan Island E116248 entity
Predicate hasSettlement P1068 FINISHED
Object Santa Fe town 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 town | Statement: [Bantayan Island, hasSettlement, Santa Fe town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Fe town
Context triple: [Bantayan Island, hasSettlement, Santa Fe town]
  • A. 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.
  • 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 historic Argentine city and provincial capital known for its colonial heritage and strategic location on the Paraná River.
  • E. 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.
  • 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_69bd445d94788190b72e2cc563120995 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd78dc329c8190808085c6b3e4241c completed March 20, 2026, 4:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfcb931f908190b72d825b95ae4861 completed March 22, 2026, 10:59 a.m.
Created at: March 20, 2026, 1:44 p.m.