Triple
T10504403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dyson Supersonic hair dryer |
E247747
|
entity |
| Predicate | heatControlMethod |
P11950
|
FINISHED |
| Object | temperature sensor with feedback loop |
—
|
LITERAL 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: temperature sensor with feedback loop | Statement: [Dyson Supersonic hair dryer, heatControlMethod, temperature sensor with feedback loop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: heatControlMethod Context triple: [Dyson Supersonic hair dryer, heatControlMethod, temperature sensor with feedback loop]
-
A.
temperatureControlMethod
chosen
Indicates the method or mechanism used to regulate or maintain a desired temperature.
-
B.
thermalControl
Indicates a relationship where one entity regulates, adjusts, or maintains the temperature or thermal conditions of another entity or environment.
-
C.
heatingMethod
Indicates the method or technique used to apply heat to something, such as for cooking, warming, or processing.
-
D.
heatTransferMethod
Indicates the mechanism or process by which heat is transferred from one entity or system to another.
-
E.
hasPlatformHeaters
Indicates that a platform is equipped with heaters to provide warmth or prevent ice and snow accumulation.
- F. None of above.
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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5099f4dec8190a9851739c8bc9a69 |
completed | April 7, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69d4fb919ea08190bcc1193e2014d437 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:26 p.m.