Triple

T12090572
Position Surface form Disambiguated ID Type / Status
Subject SMART train E287929 entity
Predicate connectsCommunity P12608 FINISHED
Object Santa Rosa E27583 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 Rosa | Statement: [SMART train, connectsCommunity, Santa Rosa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santa Rosa
Context triple: [SMART train, connectsCommunity, Santa Rosa]
  • A. Santa Rosa chosen
    Santa Rosa is a mid-sized city in Sonoma County known as a cultural and economic hub of California’s wine country.
  • B. Santa Rosa
    Santa Rosa is a residential barrio (neighborhood) within the municipality of Dorado, Puerto Rico.
  • C. Santa Rosa
    Santa Rosa is the principal city and administrative center of Argentina’s La Pampa Province, known for its role as a regional hub in the country’s central plains.
  • D. Santa Rosa
    Santa Rosa is a small settlement located on Santa Cruz Island in the Galápagos archipelago of Ecuador.
  • E. Santa Rosa
    Santa Rosa is a coastal city in southwestern Ecuador known for its agriculture, shrimp farming, and role as a commercial center in El Oro Province.
  • 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_69d6ab4964708190850585628b287b0c completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9151797988190b0d007ea806bcf02 completed April 10, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e42cd588190835b3e8160bdbba5 completed May 2, 2026, 3:54 p.m.
Created at: April 8, 2026, 9:48 p.m.