Triple
T23723827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Réunionnais people |
E586214
|
entity |
| Predicate | regionalLanguagePolicy |
P43520
|
FINISHED |
| Object | French as official language |
—
|
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: French as official language | Statement: [Réunionnais people, regionalLanguagePolicy, French as official language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionalLanguagePolicy Context triple: [Réunionnais people, regionalLanguagePolicy, French as official language]
-
A.
languagePolicyRegion
chosen
Indicates that a particular language policy applies within, or is associated with, a specific geographic or administrative region.
-
B.
recognizedRegionalLanguage
Indicates that a language holds officially recognized status within a specific region or subnational jurisdiction.
-
C.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
D.
minorityLanguagePolicy
Indicates a policy or set of rules governing the recognition, protection, and use of languages spoken by minority groups within a larger political or social context.
-
E.
subjectLanguageRegion
Indicates that the subject is associated with or uses a language specific to a particular geographic region.
- 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_69e24906fb108190a6898751e46bdc11 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b91364208190b3404534a7403e08 |
completed | April 29, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69f155e4b1148190836ede4741dcb888 |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 7:07 p.m.