Triple

T12856236
Position Surface form Disambiguated ID Type / Status
Subject CuriOdyssey E307462 entity
Predicate city P40 FINISHED
Object San Mateo E45852 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 Mateo | Statement: [CuriOdyssey, city, San Mateo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Mateo
Context triple: [CuriOdyssey, city, San Mateo]
  • A. San Mateo
    San Mateo is a landlocked municipality in the province of Rizal in the Philippines, known for its mix of suburban communities, hilly terrain, and proximity to Metro Manila.
  • B. San Mateo chosen
    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. 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.
  • D. Sunnyvale
    Sunnyvale is a major Silicon Valley city in Northern California known for its high-tech industry presence and suburban residential communities.
  • E. Sunnyvale
    Sunnyvale is a suburban town in the Dallas–Fort Worth metropolitan area known for its residential character and proximity to Dallas, Texas.
  • 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_69d7bdf5e7cc8190be357278bc5ba3bb completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970231ce48190a4eabc4b8c24a3ff completed April 10, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff3643a23481909103166abb6aaa4e completed May 9, 2026, 1:27 p.m.
Created at: April 9, 2026, 5:37 p.m.