Triple

T1475913
Position Surface form Disambiguated ID Type / Status
Subject Zigbee E30839 entity
Predicate deviceType P4634 FINISHED
Object Zigbee coordinator E30839 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: Zigbee coordinator | Statement: [Zigbee, deviceType, Zigbee coordinator]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zigbee coordinator
Context triple: [Zigbee, deviceType, Zigbee coordinator]
  • A. Zigbee chosen
    Zigbee is a low-power, wireless mesh networking standard commonly used for home automation and Internet of Things (IoT) devices.
  • B. WSN
    WSN is the standard abbreviation used for the Washington Nationals Major League Baseball team.
  • C. IEEE 802.15
    IEEE 802.15 is a family of IEEE standards that define wireless personal area networks (WPANs), including technologies like Bluetooth and other short-range, low-power wireless communications.
  • D. Cbus
    Cbus is a common nickname for Columbus, the capital and largest city of Ohio.
  • E. WirelessHART
    WirelessHART is an industrial wireless communication standard designed for reliable, secure, and interoperable field device networking in process automation environments.
  • 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_69a498fe55a88190ab7f9e40ace88e49 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c602387c8190b97a20c8e05e3d16 completed March 1, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad15ab9430819094deb90436983036 completed March 8, 2026, 6:22 a.m.
Created at: March 1, 2026, 8:11 p.m.