Triple
T19374955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LPG |
E484641
|
entity |
| Predicate | energyContentByVolume |
P130232
|
FINISHED |
| Object | about 25 MJ/L (liquid) |
—
|
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 25 MJ/L (liquid) | Statement: [LPG, energyContentByVolume, about 25 MJ/L (liquid)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: energyContentByVolume Context triple: [LPG, energyContentByVolume, about 25 MJ/L (liquid)]
-
A.
energyDensityByVolume
chosen
Indicates the amount of energy contained per unit of volume in a given system or material.
-
B.
energyDensityByMass
Indicates the amount of energy contained per unit of mass for a given substance or system.
-
C.
fuelFraction
Indicates the proportion of an object's total mass or capacity that consists of fuel.
-
D.
energyConcentration
Indicates a relationship where energy is gathered, focused, or accumulated within a specific region, object, or system.
-
E.
energyContribution
Indicates the amount or role of energy that one entity provides or contributes to another entity, process, or system.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61a5acc4481908fecfb57af16d037 |
completed | April 20, 2026, 12:21 p.m. |
| PD | Predicate disambiguation | batch_69e4fd54f8e48190956e73dd8969164a |
completed | April 19, 2026, 4:05 p.m. |
Created at: April 10, 2026, 1:35 p.m.