Triple
T957725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thread |
E20659
|
entity |
| Predicate | competesWith |
P1375
|
FINISHED |
| Object | Z-Wave |
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: Z-Wave | Statement: [Thread, competesWith, Z-Wave]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Z-Wave Context triple: [Thread, competesWith, Z-Wave]
-
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.
WirelessHART
WirelessHART is an industrial wireless communication standard designed for reliable, secure, and interoperable field device networking in process automation environments.
-
D.
Cbus
Cbus is a common nickname for Columbus, the capital and largest city of Ohio.
-
E.
Verisure
Verisure is a leading European provider of professionally monitored home and business security alarm 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3fac2bc8190a66feb70c68899b2 |
completed | March 1, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac11a212f08190ae2aad947226d09c |
completed | March 7, 2026, 11:53 a.m. |
Created at: March 1, 2026, 7:40 p.m.