Triple

T21199691
Position Surface form Disambiguated ID Type / Status
Subject Howard Bannister E522419 entity
Predicate storySetting P1957 FINISHED
Object San Francisco — 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 Francisco | Statement: [Howard Bannister, storySetting, San Francisco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San Francisco
Context triple: [Howard Bannister, storySetting, San Francisco]
  • A. 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.
  • B. 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.
  • C. San Francisco
    San Francisco is a coastal municipality in the Philippine province of Surigao del Norte, known for its island landscapes and fishing communities.
  • D. San Francisco
    San Francisco is a town located in the Atlántida Department on the northern Caribbean coast of Honduras.
  • E. San Francisco
    San Francisco is a municipality in the Philippine province of Quezon known for its rural communities and agricultural economy.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69e0b51061388190aa03f19700d3ef04 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7342fe3a08190b7ed2cadf60091a8 completed April 21, 2026, 8:24 a.m.
Created at: April 16, 2026, 3:17 p.m.