Triple
T28553231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turkish coffee |
E722941
|
entity |
| Predicate | traditionalHeatSource |
P38384
|
FINISHED |
| Object | hot sand |
—
|
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: hot sand | Statement: [Turkish coffee, traditionalHeatSource, hot sand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalHeatSource Context triple: [Turkish coffee, traditionalHeatSource, hot sand]
-
A.
heatSource
chosen
Indicates that one entity serves as a source of heat or heating for another entity.
-
B.
heatingMethod
Indicates the method or technique used to apply heat to something, such as for cooking, warming, or processing.
-
C.
primaryHeatingFuel
Indicates the type of fuel or energy source that is mainly used for heating a building or space.
-
D.
thermalPower
Indicates the amount of heat energy per unit time that a system, device, or process generates, transfers, or consumes.
-
E.
losesHeatTo
Indicates that one entity transfers thermal energy to another, resulting in a decrease in the first entity’s heat.
- 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_69f01a60204481909af1bb76247b8221 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69fd3d46d1f48190a1b20dd063224b7d |
completed | May 8, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69fd3ae1510c81908fe1280efc17feee |
completed | May 8, 2026, 1:22 a.m. |
Created at: April 28, 2026, 3:44 a.m.