Triple
T24598252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Constitution of Vanuatu |
E608741
|
entity |
| Predicate | officialLanguagesSpecified |
P236
|
FINISHED |
| Object | Bislama |
—
|
NE NERFINISHED |
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: Bislama | Statement: [Constitution of Vanuatu, officialLanguagesSpecified, Bislama]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officialLanguagesSpecified Context triple: [Constitution of Vanuatu, officialLanguagesSpecified, Bislama]
-
A.
hasLanguageOfficial
Indicates that a language holds official status within a given entity, such as a country, region, or organization.
-
B.
officialLanguage
chosen
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.
-
C.
additionalOfficialLanguage
Indicates that an entity has another language, beyond its primary one, that holds official or formally recognized status.
-
D.
haveDistinctOfficialLanguages
Indicates that the two entities each have their own official language and these official languages are not the same.
-
E.
numberOfOfficialLanguagesInCountry
Indicates the total count of officially recognized languages within a given country.
- 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_69e2c4cf54248190af7b0c2d9ade9830 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
Created at: April 18, 2026, 2:30 a.m.