Triple
T8630792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A220-100 |
E204394
|
entity |
| Predicate | fuelEfficiencyComparedToOlderJets |
P41013
|
FINISHED |
| Object | improved |
—
|
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: improved | Statement: [A220-100, fuelEfficiencyComparedToOlderJets, improved]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fuelEfficiencyComparedToOlderJets Context triple: [A220-100, fuelEfficiencyComparedToOlderJets, improved]
-
A.
comparedToOtherPlanes
Indicates a relationship where one plane is evaluated or contrasted against other planes in terms of some shared characteristic or metric.
-
B.
typicalEfficiencyComparedToPredecessor
chosen
Indicates how the usual or average efficiency of something compares to that of its predecessor.
-
C.
aircraftGeneration
Indicates a generational relationship between aircraft, such as one model being a successor, predecessor, or belonging to a specific generation relative to another.
-
D.
fuelEffect
Indicates the influence or impact that a given fuel has on a process, system, or outcome.
-
E.
emissionsComparedToPredecessor
Indicates how the emissions of an entity compare in magnitude (e.g., higher, lower, or equal) to those of its immediate predecessor.
- 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_69ca834b903c8190add96cc651e1a477 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5730309081909a9a0256c9bf5f8f |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc455906f8819082edd79cb4a1cf28 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:27 p.m.