Triple
T25040845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martu Wangka language |
E627101
|
entity |
| Predicate | hasLanguageProgram |
P6928
|
FINISHED |
| Object | language maintenance programs in Western Australia |
—
|
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: language maintenance programs in Western Australia | Statement: [Martu Wangka language, hasLanguageProgram, language maintenance programs in Western Australia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageProgram Context triple: [Martu Wangka language, hasLanguageProgram, language maintenance programs in Western Australia]
-
A.
hasEducationalProgram
Indicates that an entity offers, runs, or is associated with a specific educational program.
-
B.
hasLanguageOfStudy
Indicates that an entity studies or is engaged in learning a particular language.
-
C.
hasLanguageAcademyOrBody
Indicates that an entity is associated with, governed by, or served by a language academy or official language-regulating body.
-
D.
hasOwnLanguage
Indicates that an entity possesses or uses a distinct language of its own.
-
E.
hasProgramme
chosen
Indicates that an entity is associated with or offers a particular programme (such as a course of study, plan, or structured set of activities).
- 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_69e2ff2a2c088190be513727ee8bfe78 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f657f653448190a945b4751af8507d |
completed | May 2, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 18, 2026, 6:08 a.m.