Triple
T238249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SkyTeam |
E4870
|
entity |
| Predicate | numberOfMemberAirlines |
P9452
|
FINISHED |
| Object | 19 |
—
|
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: 19 | Statement: [SkyTeam, numberOfMemberAirlines, 19]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMemberAirlines Context triple: [SkyTeam, numberOfMemberAirlines, 19]
-
A.
servesAirlineAlliance
Indicates that an airline operates flights on behalf of, or under the branding of, a specific airline alliance.
-
B.
nationalAirline
Indicates that an airline serves as the official or primary flag carrier of a particular country.
-
C.
numberOfMemberStates
Indicates the total count of member states associated with a given entity or organization.
-
D.
hasNumberOfMemberInstitutions
Indicates the quantitative count of member institutions associated with a given entity.
-
E.
numberOfPlanes
Indicates the quantity of planes associated with or involved in a given entity or situation.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25dacf60c8190a5c3ef455b9a8b20 |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b5f27208190ae13f34037fe582b |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25dab745c8190829b7b5e915936e8 |
completed | Feb. 28, 2026, 3:14 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.