Triple

T4183979
Position Surface form Disambiguated ID Type / Status
Subject Irazú E88265 entity
Predicate locatedIn P40 FINISHED
Object Cartago Province E404969 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: Cartago Province | Statement: [Irazú, locatedIn, Cartago Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cartago Province
Context triple: [Irazú, locatedIn, Cartago Province]
  • A. Cartago Province chosen
    Cartago Province is a central region of Costa Rica known for its historic colonial capital, fertile agricultural lands, and active volcanoes such as Irazú and Turrialba.
  • B. Chiriquí Province
    Chiriquí Province is a western Panamanian province bordering Costa Rica, known for its agricultural production, mountain landscapes, and the highland town of Boquete.
  • C. Tungurahua Province
    Tungurahua Province is a central Andean province of Ecuador known for its active Tungurahua volcano, agricultural economy, and indigenous communities.
  • D. San José Province
    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.
  • E. Coclé Province
    Coclé Province is a central Panamanian province known for its Pacific coastline, agricultural production, and growing tourism centered around beaches and historical sites.
  • 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_69aed9477e8c81908bcb862d2db55b1d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0321eee88190871c1d4bf44a5007 completed March 9, 2026, 5:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69b589fe4b508190a1c5a1d426245ede completed March 14, 2026, 4:17 p.m.
Created at: March 9, 2026, 3:45 p.m.