Triple

T19323367
Position Surface form Disambiguated ID Type / Status
Subject Alviso area of San Jose E483283 entity
Predicate integratedInto P77 FINISHED
Object City of San Jose 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: City of San Jose | Statement: [Alviso area of San Jose, integratedInto, City of San Jose]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of San Jose
Context triple: [Alviso area of San Jose, integratedInto, City of San Jose]
  • A. San Jose City
    San Jose City is a landlocked component city in the province of Nueva Ecija in the Philippines, known as an agricultural and commercial hub in Central Luzon.
  • B. City of Santa Clara
    The City of Santa Clara is a municipality in California’s Silicon Valley known for its technology companies, Levi’s Stadium, and proximity to major Bay Area hubs.
  • C. San Jose chosen
    San Jose is a major technology and innovation hub in Silicon Valley and one of the largest cities in Northern California.
  • D. San Jose
    San Jose is a coastal municipality in the Philippine province of Negros Oriental known for its rural communities and proximity to Dumaguete City.
  • 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_69d8e8d13e3c81909d91d1d5ec37c095 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e60d8a07508190a2e5f8972d1efba0 completed April 20, 2026, 11:27 a.m.
Created at: April 10, 2026, 1:32 p.m.