Triple

T14632059
Position Surface form Disambiguated ID Type / Status
Subject Nokia 8150 E343501 entity
Predicate mobileNetworkTechnology P99395 FINISHED
Object GSM 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: GSM | Statement: [Nokia 8150, mobileNetworkTechnology, GSM]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: mobileNetworkTechnology
Context triple: [Nokia 8150, mobileNetworkTechnology, GSM]
  • A. networkType
    Indicates the category or kind of network associated with or used by an entity (e.g., wired, wireless, virtual, or specific protocol-based networks).
  • B. hasCellularModel
    Indicates that one entity serves as a cellular (cell-based) model or system used to study, represent, or simulate the biological properties or behavior of another entity.
  • C. cellularOptions chosen
    Indicates that one entity specifies or provides available cellular network or mobile connectivity options for another entity.
  • D. hasSIMType
    Indicates that an entity uses or is associated with a specific type or category of SIM (Subscriber Identity Module).
  • E. wirelessOperator
    Indicates that an entity operates, manages, or provides services for a wireless communication system or network for another entity.
  • 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_69d822dffc3c8190aa173b90761bffda completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4a912248190a3df7f821395c776 completed April 14, 2026, 9:42 p.m.
PD Predicate disambiguation batch_69de657359c88190b082e3e9f86fc1d7 completed April 14, 2026, 4:04 p.m.
Created at: April 10, 2026, 1:26 a.m.