Triple

T14056904
Position Surface form Disambiguated ID Type / Status
Subject City Circle Line E338241 entity
Predicate safetySystem P840 FINISHED
Object CBTC E340578 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: CBTC | Statement: [City Circle Line, safetySystem, CBTC]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: CBTC
Context triple: [City Circle Line, safetySystem, CBTC]
  • A. CBTC chosen
    CBTC (Communications-Based Train Control) is an advanced railway signalling system that uses continuous, high-capacity data communication to manage train movements with greater safety and efficiency.
  • B. CTCS-2
    CTCS-2 is a train control system level within the Chinese Train Control System hierarchy, providing a standardized, lower-tier signaling and control capability compared to CTCS-3.
  • C. Siemens Trainguard MT
    Siemens Trainguard MT is a communications-based train control (CBTC) signaling system developed by Siemens for fully automated and driverless metro and urban rail operations.
  • D. CTCS-3
    CTCS-3 is a high-level Chinese Train Control System standard used for advanced, high-speed railway signaling and train operation control.
  • E. Automatic Train Operation (ATO)
    Automatic Train Operation (ATO) is a railway control system that automates key driving functions such as acceleration, speed regulation, and braking to improve safety, efficiency, and consistency of train operations.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de3c8e6d008190af8892f34c5cefbd completed April 14, 2026, 1:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd09b7d148190ad9a146121be01f8 completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:20 p.m.