Triple
T23271068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kwanyama |
E588289
|
entity |
| Predicate | isMacrolanguageMemberOf |
P23525
|
FINISHED |
| Object | Ovambo |
—
|
NE NERFINISHED |
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: Ovambo | Statement: [Kwanyama, isMacrolanguageMemberOf, Ovambo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMacrolanguageMemberOf Context triple: [Kwanyama, isMacrolanguageMemberOf, Ovambo]
-
A.
macrolanguageMemberOf
chosen
Indicates that a language variety is classified as a member of a larger macrolanguage grouping.
-
B.
isCulturalLanguageOf
Indicates that a language serves as a primary medium of cultural expression, identity, and heritage for a particular group, community, or region.
-
C.
isWorkingLanguageOf
Indicates that a particular language is officially used as a medium of work, communication, or operation within a specified organization, institution, or context.
-
D.
macrolanguageOf
Indicates that one language functions as a macrolanguage encompassing or grouping together one or more related individual languages.
-
E.
macrolanguageGrouping
Indicates that one language is classified as part of a broader macrolanguage grouping that encompasses multiple closely related language varieties.
- 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_69e25d148adc819088efbf42672604e9 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1957418fc819085ee528622e0c6de |
completed | April 29, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69effcecabd88190856fb6e1d993e4dd |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:45 p.m.