Triple

T21365363
Position Surface form Disambiguated ID Type / Status
Subject Berryessa Creek E526895 entity
Predicate flowsThrough P225 FINISHED
Object San José, California — NE NERFINISHED

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: San José, California | Statement: [Berryessa Creek, flowsThrough, San José, California]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San José, California
Context triple: [Berryessa Creek, flowsThrough, San José, California]
  • A. San Jose, California chosen
    San Jose, California is a major Silicon Valley city in the San Francisco Bay Area known for its tech industry, suburban sprawl, and role as a cultural and economic hub of Northern California.
  • B. San Jose, California
    San Jose, California is a major Silicon Valley city in Northern California known for its tech industry, diverse population, and role as an economic and cultural hub of the region.
  • C. San Jose, California
    San Jose, California is a major Silicon Valley city in the San Francisco Bay Area, known as a global center for technology and innovation.
  • D. San Jose
    San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
  • E. San Jose
    San Jose is a coastal municipality in the province of Northern Samar in the Eastern Visayas region of the Philippines.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51d8a308190b09113b3b3f9bc15 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8b06e1ba081908a96928a65da5fa2 completed April 22, 2026, 11:26 a.m.
Created at: April 16, 2026, 5:09 p.m.