Triple

T14977579
Position Surface form Disambiguated ID Type / Status
Subject Sacramento Metropolitan Fire District E373491 entity
Predicate serviceArea P82 FINISHED
Object Rio Linda E314751 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: Rio Linda | Statement: [Sacramento Metropolitan Fire District, serviceArea, Rio Linda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rio Linda
Context triple: [Sacramento Metropolitan Fire District, serviceArea, Rio Linda]
  • A. Rio Linda chosen
    Rio Linda is a suburban community in Sacramento County, California, known for its semi-rural character and proximity to the city of Sacramento.
  • B. Rio Vista
    Rio Vista is a small city in the Sacramento–San Joaquin River Delta region of Northern California, known for its riverside location and recreational boating and fishing.
  • C. Arroyo Grande
    Arroyo Grande is a small coastal city in California known for its historic village, agricultural surroundings, and proximity to the beaches of the Central Coast.
  • D. La Cañada
    La Cañada is a town in the Mexican state of Querétaro that serves as the municipal seat of El Marqués.
  • E. Peralta
    Peralta is a town in northern Spain’s Navarre region situated along the Arga River.
  • 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_69d85ccbbcd48190acb56e7cf104d8ad completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded6fbd138819092254ea37388026c completed April 15, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe8beca6d88190a0c1adb18c9f2ac4 completed May 9, 2026, 1:20 a.m.
Created at: April 10, 2026, 2:51 a.m.