Triple

T8073056
Position Surface form Disambiguated ID Type / Status
Subject County of Orange E188421 entity
Predicate hasCountySeat P383 FINISHED
Object Santa Ana, California E34944 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 Ana, California | Statement: [County of Orange, hasCountySeat, Santa Ana, California]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Ana, California
Context triple: [County of Orange, hasCountySeat, Santa Ana, California]
  • A. Santa Ana chosen
    Santa Ana is a major city in Orange County, California, known as a dense urban and governmental center within the Greater Los Angeles metropolitan area.
  • B. Santa Ana
    Santa Ana is a barangay (village-level administrative division) within the highly urbanized city of Taguig in Metro Manila, Philippines.
  • C. Santa Ana
    Santa Ana is a town in the Francisco Morazán Department of Honduras, located in the central region of the country near the capital, Tegucigalpa.
  • D. Santa Ana
    Santa Ana is a suburban city in Costa Rica known for its upscale residential areas, commercial development, and proximity to the capital, San José.
  • E. Santa Ana
    Santa Ana is a small inhabited island in the Solomon Islands’ Makira-Ulawa Province, known for its traditional culture and coastal village communities.
  • 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_69ca82b50c708190863f661d438e68df completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb40482200819086c639f64c01fbb5 completed March 31, 2026, 3:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf278d5abc8190a9330918486e464f completed April 3, 2026, 2:35 a.m.
Created at: March 30, 2026, 5:27 p.m.