Triple
T18205583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jet-A kerosene |
E435892
|
entity |
| Predicate | energyDensityByMass |
P130231
|
FINISHED |
| Object | about 43 MJ/kg |
—
|
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: about 43 MJ/kg | Statement: [Jet-A kerosene, energyDensityByMass, about 43 MJ/kg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: energyDensityByMass Context triple: [Jet-A kerosene, energyDensityByMass, about 43 MJ/kg]
-
A.
energyConcentration
Indicates a relationship where energy is gathered, focused, or accumulated within a specific region, object, or system.
-
B.
powerDensity
Indicates the amount of power distributed per unit area or volume in a given context.
-
C.
hasOrderOfMagnitudeInJoules
Indicates that the quantity associated with an entity is approximately of a specified order of magnitude when measured in joules.
-
D.
energyContribution
Indicates the amount or role of energy that one entity provides or contributes to another entity, process, or system.
-
E.
energyPotential
Indicates a relationship where one entity possesses or confers the capacity to perform work or cause change (potential energy) relative to another entity or state.
- F. None of above. chosen
Provenance (4 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e2234b988190bbe2c2164d61f65f |
completed | April 19, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f684e48190b38c64b58c518b6a |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:32 a.m.