Triple
T29552269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kui people |
E749805
|
entity |
| Predicate | educationLanguageIssue |
P57405
|
FINISHED |
| Object | limited mother-tongue education |
—
|
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: limited mother-tongue education | Statement: [Kui people, educationLanguageIssue, limited mother-tongue education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: educationLanguageIssue Context triple: [Kui people, educationLanguageIssue, limited mother-tongue education]
-
A.
languageOfIssue
Indicates the language in which a particular item, document, or resource is issued or published.
-
B.
languageAdvocated
Indicates that an entity actively supports, promotes, or argues in favor of the use or adoption of a particular language.
-
C.
educationIssue
chosen
Indicates that there is a problem, challenge, or concern related to education affecting the entities involved.
-
D.
primaryLanguageConcerned
Indicates that the relationship or action specifically involves or pertains to the main or principal language in question.
-
E.
languageSubject
Indicates that a particular language is the subject or topic being studied, discussed, or otherwise focused on in relation to 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_69f0bd48691081908cecad39bac591e0 |
completed | April 28, 2026, 1:59 p.m. |
| NER | Named-entity recognition | batch_69f6b49436b0819094e21603054d05d4 |
completed | May 3, 2026, 2:36 a.m. |
| PD | Predicate disambiguation | batch_69f6b3a5fd8481909433e923c5e24e55 |
completed | May 3, 2026, 2:32 a.m. |
Created at: April 28, 2026, 5:13 p.m.