Triple

T7254616
Position Surface form Disambiguated ID Type / Status
Subject Carmen E157686 entity
Predicate partOf P40 FINISHED
Object San José Province E160636 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 Province | Statement: [Carmen, partOf, San José Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: San José Province
Context triple: [Carmen, partOf, San José Province]
  • A. San José Province chosen
    San José Province is a central administrative region of Costa Rica that includes the national capital and serves as a political, economic, and cultural hub of the country.
  • B. Santa Isabel Province
    Santa Isabel Province is an island province of the Solomon Islands in the southwestern Pacific Ocean, known for its indigenous cultures and tropical landscapes.
  • C. Melgar Province
    Melgar Province is an administrative division in southeastern Peru known for its high Andean landscapes and location within the Puno Region.
  • D. Heredia Province
    Heredia Province is one of Costa Rica’s central provinces, known for its colonial architecture, coffee plantations, and role as an educational hub.
  • E. San Román Province
    San Román Province is an administrative division in southern Peru known for its capital city Juliaca, a major commercial and transport hub in the Andean highlands.
  • 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_69c6882d81d4819085f7ff862951ee4f completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ea9f55b4819081a43e7a01eda154 completed March 27, 2026, 8:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c827604a808190a362734e864123aa completed March 28, 2026, 7:09 p.m.
Created at: March 27, 2026, 2:56 p.m.