Triple

T11240414
Position Surface form Disambiguated ID Type / Status
Subject Santa Ana Zoo E266058 entity
Predicate location P40 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: [Santa Ana Zoo, location, Santa Ana, California]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Ana, California
Context triple: [Santa Ana Zoo, location, 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 small inhabited island in the Solomon Islands’ Makira-Ulawa Province, known for its traditional culture and coastal village communities.
  • D. Santa Ana
    Santa Ana is a landlocked agricultural municipality in the province of Pampanga in the Philippines, known for its farming communities and local festivals.
  • E. 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.
  • 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_69d6aac656d48190b275efaa7d6074ee completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e919eaf48190a1457851cfc56afb completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4cc5bcff08190830d09c9aa0187b2 completed April 19, 2026, 12:36 p.m.
Created at: April 8, 2026, 9:30 p.m.