Triple
T36291197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ngaanyatjarra people |
E893232
|
entity |
| Predicate | traditionalLanguageType |
P200328
|
FINISHED |
| Object | Oral 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: Oral language | Statement: [Ngaanyatjarra people, traditionalLanguageType, Oral language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalLanguageType Context triple: [Ngaanyatjarra people, traditionalLanguageType, Oral language]
-
A.
traditionalLanguageName
Indicates the name traditionally used in a particular language to refer to the subject entity.
-
B.
languageTraditionally
Indicates that something is customarily or historically expressed, written, or communicated in a particular language.
-
C.
languageFamilyTraditional
Indicates that one entity belongs to, or is classified under, the traditional language family of the other entity.
-
D.
hasPrimaryTraditionalLanguage
Indicates that one entity is the main or principal traditional language associated with another entity.
-
E.
dominantTraditionalLanguage
Indicates that one language is the primary or most widely used traditional language within a given context or community.
- F. None of above. chosen
Provenance (4 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_69f76e4a61f0819084a2b68dbbb4efc6 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ff80d9a1d88190a95b1488acd6e2e5 |
completed | May 9, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69ff802ae2dc819093a3cda42b63dcbd |
completed | May 9, 2026, 6:42 p.m. |
| PDg | Predicate description generation | batch_69ff80d8ff208190b9e95d077fd99f78 |
completed | May 9, 2026, 6:45 p.m. |
Created at: May 3, 2026, 4:09 p.m.