Triple

T7492405
Position Surface form Disambiguated ID Type / Status
Subject Public Switched Telephone Network E177035 entity
Predicate usesSignalingSystem P19148 FINISHED
Object SS7 E409008 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: SS7 | Statement: [Public Switched Telephone Network, usesSignalingSystem, SS7]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SS7
Context triple: [Public Switched Telephone Network, usesSignalingSystem, SS7]
  • A. SS7 chosen
    SS7 (Signaling System No. 7) is a global telecommunications signaling protocol suite used to set up and manage telephone calls, SMS, and other network services across public switched telephone networks.
  • B. SS7 Via Appia
    SS7 Via Appia is a major Italian state highway that follows the historic route of the ancient Appian Way, connecting Rome with southern regions of the country.
  • C. Signaling System No. 7
    Signaling System No. 7 is a global telecommunications signaling protocol suite used to set up and manage telephone calls and other services across digital 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. ISUP
    ISUP is a French higher education institution in Paris specializing in advanced studies and training in statistics and actuarial science.
  • 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_69c69f2583808190bd1a4936c42a5815 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f5784c908190b701959daf082625 completed March 27, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83c76a8988190bb5ff21731b19d4b completed March 28, 2026, 8:39 p.m.
Created at: March 27, 2026, 3:43 p.m.