Triple

T6072888
Position Surface form Disambiguated ID Type / Status
Subject Greater Lima conurbation E135326 entity
Predicate containsDistrict P22582 FINISHED
Object San Miguel E442521 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 Miguel | Statement: [Greater Lima conurbation, containsDistrict, San Miguel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Miguel
Context triple: [Greater Lima conurbation, containsDistrict, San Miguel]
  • A. San Miguel
    San Miguel is a landlocked agricultural municipality in the province of Bulacan in the Philippines, known for its historical sites and rural communities.
  • B. San Miguel
    San Miguel is an active stratovolcano in eastern El Salvador, known for its frequent eruptions and prominent conical shape within the Central American volcanic chain.
  • C. San Miguel
    San Miguel is a town located within Bolívar Province in central Ecuador, known for its Andean setting and local agricultural activities.
  • D. San Miguel chosen
    San Miguel is a coastal district of Lima, Peru, known for its residential areas, shopping centers, and access to major avenues and the Pacific shoreline.
  • E. San Miguel
    San Miguel is a barangay (local administrative district) within the highly urbanized city of Taguig in Metro Manila, Philippines.
  • 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_69c00879e8048190b690717d19c5bc03 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05759d29481908912015e734ab943 completed March 22, 2026, 8:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11d3a37fc81909bbc1cdeec3205cf completed March 23, 2026, 11 a.m.
Created at: March 22, 2026, 4:11 p.m.