Triple

T30952984
Position Surface form Disambiguated ID Type / Status
Subject Pato E788596 entity
Predicate hasTrainsetConfiguration P26476 FINISHED
Object power cars at both ends with articulated trailer coaches LITERAL 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: power cars at both ends with articulated trailer coaches | Statement: [Pato, hasTrainsetConfiguration, power cars at both ends with articulated trailer coaches]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTrainsetConfiguration
Context triple: [Pato, hasTrainsetConfiguration, power cars at both ends with articulated trailer coaches]
  • A. hasRailConfiguration
    Indicates that an entity is associated with, or characterized by, a particular arrangement or setup of rails.
  • B. trainConfiguration chosen
    Indicates the specific arrangement and composition of train elements (such as locomotives and cars) used together for a particular operation or service.
  • C. hasLNGTrain
    Indicates that something possesses or is equipped with an LNG (liquefied natural gas) processing or transport train as part of its facilities or infrastructure.
  • D. hasTrainStyle
    Indicates that one entity (typically a train or rail service) is characterized by or associated with a particular style, type, or configuration of train.
  • E. numberOfTrainsetsBuilt
    Indicates the total count of trainsets that have been constructed or produced.
  • F. None of above.

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_69f224c28c1881908c33b45d689f1724 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69feabcda59481908f2bc13b46fcced1 completed May 9, 2026, 3:36 a.m.
PD Predicate disambiguation batch_69feaabd63f88190b30dcf6dd2ea39d1 completed May 9, 2026, 3:32 a.m.
Created at: April 29, 2026, 8:53 p.m.