Triple

T7930660
Position Surface form Disambiguated ID Type / Status
Subject Calico E184180 entity
Predicate city P40 FINISHED
Object South San Francisco E43102 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: South San Francisco | Statement: [Calico, city, South San Francisco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: South San Francisco
Context triple: [Calico, city, South San Francisco]
  • A. South San Francisco chosen
    South San Francisco is a city in northern San Mateo County, California, known for its industrial roots, biotech industry presence, and location just south of San Francisco.
  • B. San Mateo
    San Mateo is a city in California’s San Francisco Bay Area, known for its suburban neighborhoods, parks, and role as a commercial and residential hub on the Peninsula.
  • C. Sunnyvale
    Sunnyvale is a major Silicon Valley city in Northern California known for its high-tech industry presence and suburban residential communities.
  • D. Sunnyvale
    Sunnyvale is a suburban town in the Dallas–Fort Worth metropolitan area known for its residential character and proximity to Dallas, Texas.
  • E. San Bruno
    San Bruno is a small city in San Mateo County, California, located just south of San Francisco and known for its proximity to San Francisco International Airport and the YouTube headquarters.
  • 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_69ca8290c21c8190906a5ca6fe2b03c4 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3accc388819087065ebe7d5d9591 completed March 31, 2026, 3:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e3d6191c8190adb41feec1bfa76e completed April 5, 2026, 4:23 a.m.
Created at: March 30, 2026, 5:07 p.m.