Triple

T16986165
Position Surface form Disambiguated ID Type / Status
Subject San Miguel Department E412070 entity
Predicate capital P234 FINISHED
Object San Miguel E86876 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: [San Miguel Department, capital, San Miguel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San Miguel
Context triple: [San Miguel Department, capital, 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 chosen
    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 municipality located in Colombia’s southern Putumayo Department, near the border with Ecuador.
  • D. San Miguel
    San Miguel is a city in the Greater Buenos Aires metropolitan area of Argentina, located in the northwest of Buenos Aires Province.
  • E. San Miguel
    San Miguel is a rural municipality located on the island province of Catanduanes in the Bicol Region of the 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d27b58908190a643bcbd105b1849 completed April 18, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc1109a081908890bbd5958c76c2 completed May 10, 2026, 7:27 p.m.
Created at: April 10, 2026, 5:32 a.m.