Triple

T16955924
Position Surface form Disambiguated ID Type / Status
Subject Costa Rican Route 32 E411300 entity
Predicate abbreviation P43 FINISHED
Object Ruta 32 E1244810 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: Ruta 32 | Statement: [Costa Rican Route 32, abbreviation, Ruta 32]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ruta 32
Context triple: [Costa Rican Route 32, abbreviation, Ruta 32]
  • A. Ruta 32 chosen
    Ruta 32 is a major Costa Rican highway that connects the capital city of San José with the Caribbean port city of Limón, serving as a key route across the country’s central mountains.
  • B. Ruta 3
    Ruta 3 is a major national highway in Uruguay that runs through several departments and connects key cities in the country’s road network.
  • C. Ruta 34
    Ruta 34 is a major highway in Uruguay that serves as an important regional connector within the national road network.
  • D. Ruta 23
    Ruta 23 is a numbered highway route, likely part of a national road network that intersects with Ruta 1.
  • E. Ruta 27
    Ruta 27 is a major Costa Rican highway that connects the capital San José with the Pacific coast, serving as a key route for commerce and tourism.
  • 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_69d886c9c9d481909afe222093641cae completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d01bb700819082a441c124be3cb6 completed April 18, 2026, 6:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a015fb99b348190a6db655cd8aee799 completed May 11, 2026, 4:48 a.m.
Created at: April 10, 2026, 5:31 a.m.