Triple
T16120633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | F8 |
E391125
|
entity |
| Predicate | airlineIndustrySector |
P73989
|
FINISHED |
| Object | commercial aviation |
—
|
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: commercial aviation | Statement: [F8, airlineIndustrySector, commercial aviation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineIndustrySector Context triple: [F8, airlineIndustrySector, commercial aviation]
-
A.
airline
Indicates that an entity operates as a commercial air transport carrier providing flight services between locations.
-
B.
associatedAirlineIndustry
chosen
Indicates that there is a relationship or connection between an entity and the airline industry, such as involvement, affiliation, or relevance to that sector.
-
C.
airlineOwnerIndustry
Indicates the industry or sector in which the owner of an airline operates.
-
D.
airlineCategory
Indicates the classification or type of an airline within a defined categorization system (e.g., full-service, low-cost, regional).
-
E.
airlineType
Indicates the classification or category of an airline based on its operational or service characteristics.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e20200acac8190a47e6a917ff8dd34 |
completed | April 17, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69e1828518c48190a8ef3aaa46a1f639 |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5 a.m.