Triple
T31997357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Balangiri dialect |
E817028
|
entity |
| Predicate | hasRegionSpecificVocabulary |
P49919
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Balangiri dialect, hasRegionSpecificVocabulary, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionSpecificVocabulary Context triple: [Balangiri dialect, hasRegionSpecificVocabulary, true]
-
A.
containsRegionalVocabulary
chosen
Indicates that the subject includes vocabulary items that are specific to a particular geographic region or dialect.
-
B.
hasRegionalVariationsIn
Indicates that something exhibits different forms, versions, or characteristics depending on the geographic region.
-
C.
hasVocabularyFrom
Indicates that one entity’s vocabulary, terminology, or set of terms is derived from, based on, or taken from another entity.
-
D.
hasDistinctVocabulary
Indicates that one entity’s vocabulary is different or distinguishable from that of another entity.
-
E.
hasLinguisticVariety
Indicates that one entity possesses or exhibits a particular linguistic variety in relation to another entity or context.
- 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_69f348f8ce388190ae84376b1f348f12 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a01bb06422c819095bb42f6f3a0e801 |
completed | May 11, 2026, 11:18 a.m. |
| PD | Predicate disambiguation | batch_6a01b9991c348190ac49b65ea2fd86ed |
completed | May 11, 2026, 11:12 a.m. |
Created at: May 1, 2026, 12:14 a.m.