Triple

T20025127
Position Surface form Disambiguated ID Type / Status
Subject McEnery Convention Center E494960 entity
Predicate ownedBy P347 FINISHED
Object City of San José — 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 José | Statement: [McEnery Convention Center, ownedBy, City of San José]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: City of San José
Context triple: [McEnery Convention Center, ownedBy, City of San José]
  • 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
    San Jose is a municipality in the province of Tarlac in the Central Luzon region of the Philippines, known for its predominantly agricultural economy.
  • D. San Jose chosen
    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 Philippine province of Negros Oriental known for its rural communities and proximity to Dumaguete City.
  • 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6628b6b7c81909a660fbec9c92295 completed April 20, 2026, 5:29 p.m.
Created at: April 11, 2026, 3:35 p.m.