Triple
T19227209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | combined gas law |
E480766
|
entity |
| Predicate | usesTemperatureScale |
P89813
|
FINISHED |
| Object | absolute temperature |
—
|
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: absolute temperature | Statement: [combined gas law, usesTemperatureScale, absolute temperature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTemperatureScale Context triple: [combined gas law, usesTemperatureScale, absolute temperature]
-
A.
typicalTemperatureScale
Indicates the temperature scale (such as Celsius or Fahrenheit) that is normally used to express temperature values for the given entity or context.
-
B.
characteristicTemperatureScale
chosen
Indicates the temperature scale (e.g., Celsius, Fahrenheit, Kelvin) that is used as the standard or defining measure for a given entity or context.
-
C.
isAbsoluteTemperatureScale
Indicates that a temperature scale has an absolute zero point and measures temperature starting from that theoretical minimum.
-
D.
intervalRelationToCelsius
Indicates how a given interval or range is related to a corresponding interval or range expressed in degrees Celsius.
-
E.
hasTemperatureCategory
Indicates that an entity is associated with a specific qualitative temperature classification (e.g., hot, cold, warm).
- 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_69d8e8ccb8f48190ad420098e74fb1db |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fa9968e88190b14844715ff3aa2a |
completed | April 20, 2026, 10:06 a.m. |
| PD | Predicate disambiguation | batch_69e4dcfae6f081909cc173cf71a5005c |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:25 p.m.