Triple

T5479593
Position Surface form Disambiguated ID Type / Status
Subject SMS E123437 entity
Predicate usesNetworkType P3937 FINISHED
Object GSM network E123436 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: GSM network | Statement: [SMS, usesNetworkType, GSM network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GSM network
Context triple: [SMS, usesNetworkType, GSM network]
  • A. GSM chosen
    GSM is a second-generation (2G) digital mobile communication standard that became the global foundation for cellular voice and basic data services.
  • B. GSM
    GSM is the common abbreviation for Great St Mary’s Church, the historic University Church located in the center of Cambridge, England.
  • C. GSM core network
    The GSM core network is the central backbone of GSM mobile systems, handling key functions such as switching, mobility management, authentication, and interconnection with other networks.
  • D. GSM-R
    GSM-R is a digital radio communication system used across European railways to provide secure voice and data links between trains and railway control centers.
  • E. Mobile Networks
    Mobile Networks is a Nokia business segment focused on providing mobile telecommunications infrastructure, technologies, and services for wireless network operators.
  • 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_69bd4648883481909e9775d43300c5fa completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd964583008190bf7b94f656e4ecf2 completed March 20, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf48a001c081909b0e9f1b36fd10db completed March 22, 2026, 1:40 a.m.
Created at: March 20, 2026, 2:09 p.m.