Triple
T9079609
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rafael Hernández Airport |
E217581
|
entity |
| Predicate | hasOfficialLanguageOfOperations |
P18404
|
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: [Rafael Hernández Airport, hasOfficialLanguageOfOperations, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficialLanguageOfOperations Context triple: [Rafael Hernández Airport, hasOfficialLanguageOfOperations, Spanish]
-
A.
hasPrimaryLanguageOfOperations
Indicates that an entity conducts its main activities or operations primarily using a specified language.
-
B.
isWorkingLanguageOf
chosen
Indicates that a particular language is officially used as a medium of work, communication, or operation within a specified organization, institution, or context.
-
C.
hasLanguageOfOfficialName
Indicates that an entity’s official name is expressed in a specified language.
-
D.
officialLanguage
Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
-
E.
hasOfficerLanguage
Indicates that an officer is able or authorized to communicate in a specified language.
- 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_69ca83d7a0388190ba1af89ed7ba36f9 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc95c93ee48190842623b57e50f4cf |
completed | April 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69cc65fa79bc81908b46f05c8bba920f |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:12 p.m.