Triple
T12825427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alfonso Bonilla Aragón International Airport |
E306637
|
entity |
| Predicate | hasSecondaryLanguageForOperations |
P9103
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Alfonso Bonilla Aragón International Airport, hasSecondaryLanguageForOperations, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecondaryLanguageForOperations Context triple: [Alfonso Bonilla Aragón International Airport, hasSecondaryLanguageForOperations, English]
-
A.
hasSecondaryLanguage
chosen
Indicates that an entity possesses or uses a secondary language in addition to its primary language.
-
B.
hasPrimaryLanguageOfOperations
Indicates that an entity conducts its main activities or operations primarily using a specified language.
-
C.
hasSecondaryLanguageFamily
Indicates that an entity has an additional, non-primary association with a particular language family.
-
D.
tertiaryLanguageOfOperation
Indicates that an entity uses a specified language as its third most prominent or prioritized language of operation.
-
E.
hasSecondaryLanguageTradition
Indicates that an entity possesses an additional, non-primary language tradition associated with it, such as in its use, documentation, or cultural context.
- 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9714208f881908f7f8a921362909a |
completed | April 10, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69d96fa08cd481909a946046ba63809f |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:32 p.m.