Triple

T13143852
Position Surface form Disambiguated ID Type / Status
Subject Empresa de los Ferrocarriles del Estado E312284 entity
Predicate hasSubsidiary P254 FINISHED
Object Biotrén E312286 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: Biotrén | Statement: [Empresa de los Ferrocarriles del Estado, hasSubsidiary, Biotrén]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Biotrén
Context triple: [Empresa de los Ferrocarriles del Estado, hasSubsidiary, Biotrén]
  • A. Biotrén chosen
    Biotrén is a suburban commuter rail system serving the Greater Concepción area in southern Chile.
  • B. Treniota
    Treniota was a 13th-century Lithuanian noble who briefly ruled as Grand Duke after orchestrating the assassination of his uncle, King Mindaugas, and leading pagan resistance against Christianization.
  • C. Megatren
    Megatren is the local name for Manila’s LRT Line 2, an elevated rapid transit line serving key east–west corridors in Metro Manila, Philippines.
  • D. Tsalka
    Tsalka is a town in southern Georgia known for its ethnically diverse population and its location near the Tsalka Reservoir in the Kvemo Kartli region.
  • E. Kogon
    Kogon is a small city in Uzbekistan known for its location near the historic center of Bukhara and its role as a local transport and industrial hub.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98bce3678819082a7aa1d83f20592 completed April 10, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eae4a87881908be57e15f001c904 completed May 3, 2026, 6:27 a.m.
Created at: April 9, 2026, 9:10 p.m.