Triple

T21276062
Position Surface form Disambiguated ID Type / Status
Subject 3GPP TS 24.008 E524389 entity
Predicate usedIn P98 FINISHED
Object GSM/EDGE networks NE NERFINISHED

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/EDGE networks | Statement: [3GPP TS 24.008, usedIn, GSM/EDGE networks]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GSM/EDGE networks
Context triple: [3GPP TS 24.008, usedIn, GSM/EDGE networks]
  • A. GSM EDGE Radio Access Network chosen
    GSM EDGE Radio Access Network (GERAN) is a 2G/2.5G mobile telecommunications radio access technology that enhances GSM networks with higher data rates using EDGE modulation.
  • B. GSM
    GSM is a second-generation (2G) digital mobile communication standard that became the global foundation for cellular voice and basic data services.
  • C. GSM
    GSM is a classic Onitsuka Tiger sneaker model inspired by vintage tennis shoes, known for its minimalist design and retro athletic style.
  • D. GSM
    GSM is the three-letter IATA airport code assigned to Qeshm International Airport in Iran.
  • E. GSM
    GSM is the common abbreviation for Great St Mary’s Church, the historic University Church located in the center of Cambridge, England.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b516293c819089458ea2ec85f85e completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e736577fd48190a0038a6ac5678668 completed April 21, 2026, 8:33 a.m.
Created at: April 16, 2026, 4:02 p.m.