Triple
T34051675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GEC |
E873239
|
entity |
| Predicate | airlineTypeDesignated |
P78265
|
FINISHED |
| Object | cargo airline |
—
|
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: cargo airline | Statement: [GEC, airlineTypeDesignated, cargo airline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineTypeDesignated Context triple: [GEC, airlineTypeDesignated, cargo airline]
-
A.
designatedAirlineType
chosen
Indicates that an airline has been assigned a specific operational or classification type for a given context or service.
-
B.
airlineDesignatorType
Indicates the type or category of an airline’s designator code used to identify the carrier in transportation or scheduling contexts.
-
C.
airlineType
Indicates the classification or category of an airline based on its operational or service characteristics.
-
D.
servesAirlineType
Indicates that a service provider (such as an airport, terminal, or facility) accommodates or operates flights for a specified type or category of airline.
-
E.
airlineFleetDesignation
Indicates the specific fleet or operational group within an airline to which an aircraft or service is assigned.
- 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_69f349a3ec2c8190b62da76e54231a0f |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70fb4f18c819099ef6d9177b7d205 |
completed | May 3, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f70f3a54d481909ba6bdda3647b761 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:51 a.m.