Triple

T12345232
Position Surface form Disambiguated ID Type / Status
Subject Col. Bonny Serrano Avenue E294335 entity
Predicate locatedInCity P40 FINISHED
Object San Juan E274337 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 Juan | Statement: [Col. Bonny Serrano Avenue, locatedInCity, San Juan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Juan
Context triple: [Col. Bonny Serrano Avenue, locatedInCity, San Juan]
  • A. San Juan
    San Juan is a coastal municipality on Siquijor Island in the Philippines known for its beaches, dive spots, and laid-back tourist resorts.
  • B. San Juan
    San Juan is the largest city and main cultural, economic, and tourism hub of Puerto Rico, known for its historic colonial architecture and vibrant coastal setting.
  • C. San Juan chosen
    San Juan is a highly urbanized city in Metro Manila, Philippines, known for its historical sites, dense residential and commercial areas, and role in the capital region’s urban core.
  • D. San Juan
    San Juan is a neighborhood within the municipality of Telde on the island of Gran Canaria in Spain’s Canary Islands.
  • E. San Juan
    San Juan is a coastal municipality in the Philippine province of Batangas known for its beaches, dive spots, and heritage sites.
  • 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_69d6ab6ccbec8190b09e2d357aa80064 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f7a4a448190aa70d66dc2f406c1 completed April 10, 2026, 6:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64b8ed1dc81908a0066d7cbfda086 completed May 2, 2026, 7:07 p.m.
Created at: April 8, 2026, 9:53 p.m.