Triple
T1959663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aeropuertos y Servicios Auxiliares |
E42351
|
entity |
| Predicate | publicOwnership |
P12336
|
FINISHED |
| Object | 100% government-owned |
—
|
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: 100% government-owned | Statement: [Aeropuertos y Servicios Auxiliares, publicOwnership, 100% government-owned]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicOwnership Context triple: [Aeropuertos y Servicios Auxiliares, publicOwnership, 100% government-owned]
-
A.
ownedProperty
Indicates that one entity possesses legal ownership or control over another entity as property.
-
B.
privateOwnershipShare
Indicates the proportion or share of ownership in an entity that is held by private (non-governmental) owners.
-
C.
ownershipType
Indicates the specific nature or category of the ownership relationship that one entity holds over another.
-
D.
publicOwnershipShare
chosen
Indicates the proportion of an entity that is owned by public shareholders or the general public, as opposed to private or insider ownership.
-
E.
ownsOrManages
Indicates that one entity has ownership of, or managerial control over, another 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_69a8870eea088190a38781990812a9bc |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb68a8e608190bc37a85913b3cd44 |
completed | March 7, 2026, 5:24 a.m. |
| PD | Predicate disambiguation | batch_69abaff5dbd48190a9d36ca60de151db |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:36 p.m.