Triple

T13241723
Position Surface form Disambiguated ID Type / Status
Subject CAN bus E315294 entity
Predicate relatedStandard P37 FINISHED
Object DeviceNet E924836 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: DeviceNet | Statement: [CAN bus, relatedStandard, DeviceNet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DeviceNet
Context triple: [CAN bus, relatedStandard, DeviceNet]
  • A. DeviceNet chosen
    DeviceNet is an industrial fieldbus network protocol used primarily for connecting industrial controllers with I/O devices, drives, and other automation components over a robust, real-time communication network.
  • B. EtherNet/IP
    EtherNet/IP is an industrial Ethernet network protocol widely used for real-time control and data exchange in automation systems, based on the Common Industrial Protocol (CIP).
  • C. MicroLogix
    MicroLogix is a family of compact programmable logic controllers (PLCs) from Rockwell Automation designed for small to mid-sized industrial control and automation applications.
  • D. EtherCAT
    EtherCAT is a high-performance industrial Ethernet protocol designed for real-time control in automation systems.
  • E. Sercos III
    Sercos III is a real-time industrial Ethernet communication standard widely used for high-performance motion control and automation systems.
  • 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d59e84c8190a9e547d0fe26a5f9 completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff3438888190b4aecb0b67153ed9 completed May 3, 2026, 7:54 a.m.
Created at: April 9, 2026, 9:23 p.m.