Triple
T27294398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orange Cay |
E688721
|
entity |
| Predicate | hasPrimaryLanguageOfSovereignState |
P83252
|
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: [Orange Cay, hasPrimaryLanguageOfSovereignState, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryLanguageOfSovereignState Context triple: [Orange Cay, hasPrimaryLanguageOfSovereignState, English]
-
A.
usesOfficialLanguageOf
Indicates that one entity adopts and employs the official language of another entity for communication or formal purposes.
-
B.
hasOfficialLanguageOfSurroundingCountry
Indicates that an entity uses as its official language the same language that is official in the country surrounding it.
-
C.
hasNotableLanguageWithOfficialStatusIn
Indicates that a language holds an officially recognized and notable status within a specified jurisdiction or region.
-
D.
hasPrimaryLanguage1
chosen
Indicates that an entity’s main or most commonly used language is the specified language.
-
E.
languageOfCountryOfCitizenship
Indicates the language associated with the country where an entity holds citizenship.
- 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_69ef355a96308190a2bed991525fb278 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69fdd5fba5048190b7d430ae2054a1fd |
completed | May 8, 2026, 12:24 p.m. |
| PD | Predicate disambiguation | batch_69fdd35f76f88190a1854ea27132f9c7 |
completed | May 8, 2026, 12:13 p.m. |
Created at: April 27, 2026, 11:17 a.m.