Triple

T14794858
Position Surface form Disambiguated ID Type / Status
Subject Caldas E347746 entity
Predicate hasMunicipality P847 FINISHED
Object San José E210729 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 José | Statement: [Caldas, hasMunicipality, San José]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San José
Context triple: [Caldas, hasMunicipality, San José]
  • A. San José
    San José is a station on the Buenos Aires Underground, part of the city’s rapid transit network in Argentina.
  • B. San José
    San José is a small coastal village in Spain’s Cabo de Gata-Níjar Natural Park, known for its picturesque beaches, whitewashed houses, and role as a gateway to the park’s protected landscapes.
  • C. San José
    San José is the capital and largest city of Costa Rica, known for its political, economic, and cultural significance in Central America.
  • D. San José chosen
    San José is a small municipality and town located in the Caldas Department of Colombia, known for its coffee-growing rural landscape in the Andean region.
  • E. San José
    San José was a Spanish warship famously captured by Admiral Horatio Nelson during a daring boarding action in the late 18th century.
  • 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_69d822ea8b7c819097dfadf3d45545e6 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decd5fdd548190a2ee5e668c2b20b4 completed April 14, 2026, 11:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24bea4408190975f4856cc02580e completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:31 a.m.