Triple
T36794849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aerovías de Integración Regional S.A. |
E909154
|
entity |
| Predicate | languageOfCommercialName |
P15
|
FINISHED |
| Object | Spanish |
—
|
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: Spanish | Statement: [Aerovías de Integración Regional S.A., languageOfCommercialName, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfCommercialName Context triple: [Aerovías de Integración Regional S.A., languageOfCommercialName, Spanish]
-
A.
languageOfWorkOrName
chosen
Indicates the language in which a work is created or a name is expressed.
-
B.
multilingualName
Indicates that an entity has one or more names expressed in multiple natural languages.
-
C.
officialLanguageOfBranding
Indicates that a particular language is used as the official or primary language in the branding or marketing materials of an entity.
-
D.
marketNameLanguage
Indicates the language in which a market’s name is expressed or recorded.
-
E.
languageCommonlyCalled
Indicates that one language is commonly referred to or known by a particular alternative name or label.
- 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_69f76e7b98888190899b6478a82ad6ae |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a0149447e448190b0480943de0691ee |
completed | May 11, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_6a0148e2c39c8190a3ad6ea6be902c04 |
completed | May 11, 2026, 3:11 a.m. |
Created at: May 3, 2026, 4:12 p.m.