Triple

T10258103
Position Surface form Disambiguated ID Type / Status
Subject Juan Santamaría International Airport E240525 entity
Predicate cityServed P82 FINISHED
Object San José E29798 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: [Juan Santamaría International Airport, cityServed, San José]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San José
Context triple: [Juan Santamaría International Airport, cityServed, San José]
  • A. San José chosen
    San José is the capital and largest city of Costa Rica, known for its political, economic, and cultural significance in Central America.
  • B. San José
    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.
  • C. San José
    San José is a station on the Buenos Aires Underground, part of the city’s rapid transit network in Argentina.
  • D. San Jose City
    San Jose City is a landlocked component city in the province of Nueva Ecija in the Philippines, known as an agricultural and commercial hub in Central Luzon.
  • E. San Jose
    San Jose is the main town on the island of Tinian in the Northern Mariana Islands, serving as its administrative and population center.
  • 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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d24de4588190b68fb3daa36dbd7d completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d74ff21edc8190b8b4a6967510a869 completed April 9, 2026, 7:06 a.m.
Created at: April 6, 2026, 11:31 a.m.