Triple

T22986079
Position Surface form Disambiguated ID Type / Status
Subject Camarones E571610 entity
Predicate lineTerminusDirection2 P92985 FINISHED
Object Barranca del Muerto NE NERFINISHED

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: Barranca del Muerto | Statement: [Camarones, lineTerminusDirection2, Barranca del Muerto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barranca del Muerto
Context triple: [Camarones, lineTerminusDirection2, Barranca del Muerto]
  • A. Barranca del Muerto chosen
    Barranca del Muerto is a Mexico City Metro station in the south of the city that serves as the southern terminus of Line 7.
  • B. Barranco del Infierno
    Barranco del Infierno is a popular hiking ravine in Tenerife’s Adeje region, known for its dramatic cliffs, rich biodiversity, and scenic waterfall.
  • C. Barranca
    Barranca is a coastal city in northern Lima Region, Peru, known as a provincial capital and agricultural and commercial hub.
  • D. Cañon del Duende
    Cañon del Duende is a striking, narrow red-rock canyon near Tupiza, Bolivia, known for its dramatic cliffs and scenic hiking routes through colorful Andean landscapes.
  • E. Valle de la Barranca
    Valle de la Barranca is a scenic mountain valley in Spain’s Sierra de Guadarrama known for its pine forests, hiking trails, and views of nearby peaks.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245b3c50481908bb3741ec9f40862 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f182996ee08190ab74014ee7ecac2b completed April 29, 2026, 4:01 a.m.
Created at: April 17, 2026, 3:49 p.m.