Triple
T24748265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trond Vernegg |
E619064
|
entity |
| Predicate | languageAdvocacyFor |
P75229
|
FINISHED |
| Object | Riksmål |
—
|
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: Riksmål | Statement: [Trond Vernegg, languageAdvocacyFor, Riksmål]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageAdvocacyFor Context triple: [Trond Vernegg, languageAdvocacyFor, Riksmål]
-
A.
languageAdvocated
chosen
Indicates that an entity actively supports, promotes, or argues in favor of the use or adoption of a particular language.
-
B.
languageRights
Indicates that certain individuals or groups are entitled to use, maintain, or receive services in a particular language under recognized rights or protections.
-
C.
languageSubject
Indicates that a particular language is the subject or topic being studied, discussed, or otherwise focused on in relation to another entity.
-
D.
languageConsultant
Indicates that one entity serves as a language consultant, providing expert advice or guidance on language-related matters to another entity.
-
E.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
- 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_69e2fabb349881908a13a212a0221a63 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f62d89b89c8190afb372a8172111e7 |
completed | May 2, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69f62c1379f08190836c3e02b0c892df |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 18, 2026, 4:23 a.m.