Triple
T9240520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FV |
E222045
|
entity |
| Predicate | airlineDesignatorType |
P87732
|
FINISHED |
| Object | two-letter code |
—
|
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: two-letter code | Statement: [FV, airlineDesignatorType, two-letter code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineDesignatorType Context triple: [FV, airlineDesignatorType, two-letter code]
-
A.
designatedAirlineType
Indicates that an airline has been assigned a specific operational or classification type for a given context or service.
-
B.
airlineType
Indicates the classification or category of an airline based on its operational or service characteristics.
-
C.
representsAirline
Indicates that one entity serves as the airline associated with, operating, or branding the other entity (such as a flight, route, or service).
-
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.
airlineBrand
Indicates that one entity functions as the commercial airline brand associated with, or operating under, another entity.
- 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_69ca83ee26cc81909ac624e190597d6d |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccf0a3888c8190b72d8d0b850bdfbc |
completed | April 1, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69cc7a4765648190aa9445c4a22dc471 |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc95597be081908ece2491dd2f0f74 |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:30 p.m.