Triple

T19674679
Position Surface form Disambiguated ID Type / Status
Subject Gran Santiago metropolitan area E472421 entity
Predicate includesMunicipality P14658 FINISHED
Object San Bernardo 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 Bernardo | Statement: [Gran Santiago metropolitan area, includesMunicipality, San Bernardo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Bernardo
Context triple: [Gran Santiago metropolitan area, includesMunicipality, San Bernardo]
  • A. San Bernardo chosen
    San Bernardo is a commune and city in Chile that forms part of the Greater Santiago urban area and serves as an important residential and industrial hub.
  • B. San Bernardo
    San Bernardo is a major transport hub and metro station in Seville, Spain, serving as an interchange between urban rail, tram, and bus services.
  • C. San Bernardo
    San Bernardo is a Madrid Metro station serving the central Chamberí district and providing access to nearby residential and commercial areas.
  • D. Saint Bernard
    Saint Bernard is a coastal municipality in the province of Southern Leyte in the Philippines, known for its fishing communities and vulnerability to landslides and typhoons.
  • E. Saint Bernard
    The Saint Bernard is a large, gentle Swiss working dog breed historically famed for rescuing travelers in the Alps.
  • 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_69d8e514f2e08190ba70a4449519d218 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e641bb2b7c8190b2badf12ce2caa52 completed April 20, 2026, 3:09 p.m.
Created at: April 10, 2026, 1:45 p.m.