Triple
T10585838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EgyptAir Holding Company |
E249850
|
entity |
| Predicate | hasNumberOfSubsidiaries |
P17464
|
FINISHED |
| Object | more than 7 |
—
|
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: more than 7 | Statement: [EgyptAir Holding Company, hasNumberOfSubsidiaries, more than 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfSubsidiaries Context triple: [EgyptAir Holding Company, hasNumberOfSubsidiaries, more than 7]
-
A.
hasSubsidiaryBusiness
Indicates that one business entity owns or controls another business entity as its subsidiary.
-
B.
hasSubsidiaryLabel
Indicates that one entity is identified as a subsidiary or subordinate organization of another entity.
-
C.
hasSubsidiaryFounded
Indicates that one entity has a subsidiary that was founded or established by another specified entity.
-
D.
hasNumberOfCompanies
chosen
Indicates the quantitative relationship specifying how many companies are associated with a given entity.
-
E.
hasBranchOffice
Indicates that one organization maintains a branch office or subsidiary location in another place or entity.
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d527698be48190a2f5e573d7cc0661 |
completed | April 7, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69d51907b2b881908ab9a8594688ee06 |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:39 p.m.