Triple
T7188624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | kelvin |
E167630
|
entity |
| Predicate | exampleBoilingPointOfWater |
P19717
|
FINISHED |
| Object | approximately 373.15 K at 1 atm |
—
|
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: approximately 373.15 K at 1 atm | Statement: [kelvin, exampleBoilingPointOfWater, approximately 373.15 K at 1 atm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exampleBoilingPointOfWater Context triple: [kelvin, exampleBoilingPointOfWater, approximately 373.15 K at 1 atm]
-
A.
boilingPoint
chosen
Indicates the temperature at which a substance changes from liquid to gas under specified pressure conditions.
-
B.
meltingPoint
Indicates the temperature at which a substance changes from solid to liquid under specified conditions.
-
C.
brewingTemperature
Indicates the specific temperature at which a brewing process is carried out.
-
D.
hasBoilingCenter
Indicates that something possesses or contains a central region or core area where boiling occurs.
-
E.
waterTemperatureType
Indicates the classification or category of a water body’s temperature (e.g., cold, warm, hot) associated with an entity or context.
- 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_69c6888b5248819090499a884ee3ec39 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e8e3d9188190ba2792098d76fb86 |
completed | March 27, 2026, 8:30 p.m. |
| PD | Predicate disambiguation | batch_69c6e752385c819096fbab55566ee2a8 |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:50 p.m.