Triple

T37658869
Position Surface form Disambiguated ID Type / Status
Subject Nokia Asha 200 E937667 entity
Predicate hasFMRadioRecording P107842 FINISHED
Object yes 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: yes | Statement: [Nokia Asha 200, hasFMRadioRecording, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasFMRadioRecording
Context triple: [Nokia Asha 200, hasFMRadioRecording, yes]
  • A. hasFMTransmitter
    Indicates that one entity is equipped with or includes an FM radio transmitter component or capability.
  • B. hasAnalogRecordingCapabilities
    Indicates that an entity is capable of making or handling recordings using analog (non-digital) technology.
  • C. hasVoiceRecorder chosen
    Indicates that one entity possesses or is equipped with a voice recording device or capability in relation to another entity or context.
  • D. hasNumberOfFMChannels
    Indicates the relationship that specifies how many FM (frequency modulation) channels are associated with or supported by an entity.
  • E. supportsStereoFMRadio
    Indicates that the subject device is capable of receiving and playing stereo FM radio broadcasts.
  • 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_69f76ed6df7c8190b018e5baea716ceb completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbaa1321b48190af92a3e7ec24ec5b completed May 6, 2026, 8:52 p.m.
PD Predicate disambiguation batch_69fba8860f98819080b7bab05837b974 completed May 6, 2026, 8:45 p.m.
Created at: May 3, 2026, 4:18 p.m.