Triple

T16955902
Position Surface form Disambiguated ID Type / Status
Subject Ruta 1 E411299 entity
Predicate passesThrough P225 FINISHED
Object Esparza E1237360 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: Esparza | Statement: [Ruta 1, passesThrough, Esparza]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Esparza
Context triple: [Ruta 1, passesThrough, Esparza]
  • A. Esparza chosen
    Esparza is a canton in Costa Rica’s Puntarenas province known for its coastal location, historical town center, and role as a transit point between the Central Valley and the Pacific coast.
  • B. Valladares
    Valladares is a Spanish surname historically associated with nobility and notable figures such as colonial administrators and politicians.
  • C. Rivas
    Rivas is a city in southwestern Nicaragua known as a regional commercial center and gateway between Lake Nicaragua and the Pacific coast.
  • D. La Serna
    La Serna is a station on Madrid Metro’s Line C-5 commuter rail corridor serving the Fuenlabrada area in the Community of Madrid, Spain.
  • E. Osuna
    Osuna is a historic town in the province of Seville, Spain, known for its rich archaeological heritage, including notable ancient reliefs and other Roman-era remains.
  • 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_6a00dc06e6b481908d8032f5772762c9 completed May 10, 2026, 7:27 p.m.
Created at: April 10, 2026, 5:31 a.m.