Triple

T17376212
Position Surface form Disambiguated ID Type / Status
Subject Calle San José E422444 entity
Predicate locatedIn P40 FINISHED
Object San Juan — 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 Juan | Statement: [Calle San José, locatedIn, San Juan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: San Juan
Context triple: [Calle San José, locatedIn, San Juan]
  • A. San Juan chosen
    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.
  • B. San Juan
    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.
  • C. 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.
  • 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 (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_69d889d6535c81908be333c01deaec4e completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a6ddbd081908908b953597977d2 completed April 19, 2026, 2:14 a.m.
Created at: April 10, 2026, 5:45 a.m.