Triple

T5198943
Position Surface form Disambiguated ID Type / Status
Subject Folsom Prison Blues E117344 entity
Predicate hasTrainImagery P17123 FINISHED
Object train passing by the prison 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: train passing by the prison | Statement: [Folsom Prison Blues, hasTrainImagery, train passing by the prison]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasTrainImagery
Context triple: [Folsom Prison Blues, hasTrainImagery, train passing by the prison]
  • A. usesImageryOf chosen
    Indicates that one entity employs or incorporates visual or sensory imagery that depicts, references, or symbolically represents another entity.
  • B. hasTramway
    Indicates that a location or area is served by, contains, or is connected to a tramway system.
  • C. hasRailRoute
    Indicates that there exists a rail-based transportation route or connection between the related entities.
  • D. hasRailTrail
    Indicates that one location or entity possesses, includes, or is connected by a rail trail (a recreational trail converted from or running along a former or existing railway corridor) to another location or entity.
  • E. hasGroundTransportation
    Indicates that an entity provides, includes, or is connected to transportation services or options that operate on land (e.g., cars, buses, trains).
  • 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_69bd4462ed04819084fcb01eb9d2fa74 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7adb034c819086bf8a85fbf158f4 completed March 20, 2026, 4:50 p.m.
PD Predicate disambiguation batch_69bd77b9a67c8190819612257ea746b4 completed March 20, 2026, 4:37 p.m.
Created at: March 20, 2026, 1:47 p.m.