Triple
T475322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airbus A320 family |
E9047
|
entity |
| Predicate | hasVariantSeries |
P13477
|
FINISHED |
| Object | ceo (current engine option) |
—
|
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: ceo (current engine option) | Statement: [Airbus A320 family, hasVariantSeries, ceo (current engine option)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVariantSeries Context triple: [Airbus A320 family, hasVariantSeries, ceo (current engine option)]
-
A.
hasVariant
Indicates that one entity exists as an alternative form, version, or variation of another entity.
-
B.
isSeriesOf
Indicates that one entity is a sequence or set of related items that collectively form a series associated with another entity.
-
C.
hasParentSeries
Indicates that a work or item belongs to, or is derived from, a broader parent series.
-
D.
numberOfSeries
Indicates the total count of distinct series associated with or contained within a given entity.
-
E.
hasVariantSpelling
Indicates that one term is an alternative spelling form of another term.
- 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_69a2e7ff81708190b0507a24a997232c |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f03b5e5081908ee3dba9d19a6871 |
completed | Feb. 28, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69a2edeed31881908cf43beed410572d |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eeba8a488190986cc7381332f783 |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.