Triple
T7716147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MEA |
E174887
|
entity |
| Predicate | languageOfOperatingAirline |
P33549
|
FINISHED |
| Object | Arabic |
—
|
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: Arabic | Statement: [MEA, languageOfOperatingAirline, Arabic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfOperatingAirline Context triple: [MEA, languageOfOperatingAirline, Arabic]
-
A.
airlinePrimaryLanguage
Indicates the main language used by an airline for its official communication and operations.
-
B.
languageOfCommunications
chosen
Indicates that a specified language is used as the medium for communications associated with an entity or interaction.
-
C.
airlineType
Indicates the classification or category of an airline based on its operational or service characteristics.
-
D.
airlineBrand
Indicates that one entity functions as the commercial airline brand associated with, or operating under, another entity.
-
E.
operatedForAirline
Indicates that an aircraft or flight was operated on behalf of, or under the branding of, a particular airline.
- 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_69c6995c463c8190a14458036249d419 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702ebb7448190ae8d47fe0cbb0907 |
completed | March 27, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69c701683dec8190be9861e592aa8ce0 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:04 p.m.