Triple
T33751600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Datooga language |
E864855
|
entity |
| Predicate | hasDialectDiversity |
P66705
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Datooga language, hasDialectDiversity, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDialectDiversity Context triple: [Datooga language, hasDialectDiversity, high]
-
A.
hasNumberOfDialects
chosen
Indicates the relationship between a language (or linguistic entity) and the count of distinct dialects it possesses.
-
B.
hasDialects
Indicates that an entity (typically a language) possesses one or more distinct dialectal varieties.
-
C.
hasDialectsIn
Indicates that a language or linguistic variety possesses distinct dialects that are used or found within a specified region or context.
-
D.
hasParticularDialect
Indicates that an entity uses, is associated with, or is characterized by a specific dialect of a language.
-
E.
hadLanguageDiversity
Indicates that an entity exhibited a range of different languages used or represented within it.
- 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_69f3498c35f881909df279ae4270f831 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fee691952c8190822da83e46311d1d |
completed | May 9, 2026, 7:47 a.m. |
| PD | Predicate disambiguation | batch_69fee62f285c8190a625562a9b80526e |
completed | May 9, 2026, 7:45 a.m. |
Created at: May 1, 2026, 1:45 a.m.