Triple

T18328157
Position Surface form Disambiguated ID Type / Status
Subject Centro Empresarial Real E439066 entity
Predicate district P2709 FINISHED
Object San Isidro 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 Isidro | Statement: [Centro Empresarial Real, district, San Isidro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Isidro
Context triple: [Centro Empresarial Real, district, San Isidro]
  • A. San Isidro chosen
    San Isidro is an affluent historic city and suburban district in the Greater Buenos Aires area, known for its colonial architecture, racetrack, and riverside setting along the Río de la Plata.
  • B. San Isidro
    San Isidro is a barangay within the coastal industrial municipality of Mariveles in Bataan, Philippines.
  • C. San Isidro
    San Isidro is a coastal municipality in the province of Northern Samar in the Philippines, known for its rural communities and fishing-based local economy.
  • D. San Isidro
    San Isidro is a municipality in the Philippine province of Abra, known as a small rural local government unit in the Cordillera Administrative Region.
  • E. San Isidro
    San Isidro is a rural municipality in the Philippine province of Isabela, known primarily for its agricultural communities and rice farming.
  • 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_69d8b916a2d081909e249e4902f6aad9 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50aac14488190840b9c22209f13d1 completed April 19, 2026, 5:02 p.m.
Created at: April 10, 2026, 10:36 a.m.