Triple
T12323507
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AWS IoT Core |
E293775
|
entity |
| Predicate | hasComponent |
P35
|
FINISHED |
| Object | AWS IoT Core registry |
E293775
|
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: AWS IoT Core registry | Statement: [AWS IoT Core, hasComponent, AWS IoT Core registry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AWS IoT Core registry Context triple: [AWS IoT Core, hasComponent, AWS IoT Core registry]
-
A.
AWS IoT Core
chosen
AWS IoT Core is a managed cloud service that securely connects and manages Internet of Things devices at scale, enabling them to interact with cloud applications and other devices.
-
B.
AWS IoT Analytics
AWS IoT Analytics is a fully managed AWS service that collects, processes, enriches, and analyzes large volumes of IoT device data at scale.
-
C.
Azure IoT Hub
Azure IoT Hub is a managed cloud service for securely connecting, monitoring, and controlling large fleets of Internet of Things (IoT) devices at scale.
-
D.
IOT
IOT is the three-letter ISO 3166-1 alpha-3 country code assigned to the British Indian Ocean Territory.
-
E.
MindSphere
MindSphere is Siemens' cloud-based industrial Internet of Things (IIoT) platform for connecting, monitoring, and analyzing data from industrial equipment and 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f4d7dac81909ff10e64e229ef33 |
completed | April 10, 2026, 6:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e8d27288190bdf32acd600141db |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:53 p.m.