Triple
T19882191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General Roca Airport |
E477802
|
entity |
| Predicate | governingCountryLanguage |
P137689
|
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: [General Roca Airport, governingCountryLanguage, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: governingCountryLanguage Context triple: [General Roca Airport, governingCountryLanguage, Spanish]
-
A.
governingLanguage
Indicates the language that holds official or authoritative status over a given entity, such as a region, organization, or document.
-
B.
countryOfLanguage
Indicates that a particular language is officially or predominantly used within a specified country.
-
C.
languageOfCountryOfCitizenship
Indicates the language associated with the country where an entity holds citizenship.
-
D.
hasOfficialCountryLanguage
Indicates that a country recognizes a particular language as one of its official languages for governmental or legal purposes.
-
E.
primaryLanguageCountry
Indicates that a given language is the main or officially predominant language used within a particular country.
- 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_69d8e51f32b08190b3687f4f60353250 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658e0ccc88190b6f093035cd6f2a1 |
completed | April 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:52 p.m.