Triple

T10649632
Position Surface form Disambiguated ID Type / Status
Subject Frank Bullitt E250927 entity
Predicate workLocation P7 FINISHED
Object San Francisco E242 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: San Francisco | Statement: [Frank Bullitt, workLocation, San Francisco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Francisco
Context triple: [Frank Bullitt, workLocation, San Francisco]
  • A. San Francisco chosen
    San Francisco is a major coastal city in Northern California known for its hilly landscape, iconic Golden Gate Bridge, and role as a historic center of technology and counterculture.
  • B. San Francisco
    San Francisco is a coastal neighborhood of the city of Telde in Gran Canaria, Spain, known for its traditional Canarian architecture and historic character.
  • C. San Francisco
    San Francisco is a municipality in Colombia’s Putumayo Department, located in the southwestern part of the country near the Andean and Amazonian regions.
  • D. San Francisco
    San Francisco is a coastal municipality in the province of Southern Leyte in the Philippines, known for its rural communities and proximity to the Bohol Sea.
  • E. San Fransokyo
    San Fransokyo is a fictional futuristic hybrid city combining elements of San Francisco and Tokyo, serving as the primary setting of Disney's animated film "Big Hero 6."
  • 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_69d6aa5a4c4881908f39be6efe5981e5 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfe4b97081908815b77612222318 completed April 8, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69dbace2a5388190bb685d347dd8aa6c completed April 12, 2026, 2:32 p.m.
Created at: April 8, 2026, 9:06 p.m.