Triple
T25688903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bantu zone U |
E644145
|
entity |
| Predicate | hasLanguageMember |
P7390
|
FINISHED |
| Object | Umbundu |
—
|
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: Umbundu | Statement: [Bantu zone U, hasLanguageMember, Umbundu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageMember Context triple: [Bantu zone U, hasLanguageMember, Umbundu]
-
A.
hasMemberLanguage
chosen
Indicates that one entity is a language that is a constituent or member of a larger language group, family, or collection represented by the other entity.
-
B.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
C.
hasLanguageType
Indicates that an entity is associated with a particular type or category of language (e.g., spoken, written, programming, sign).
-
D.
hasLanguageRepresentation
Indicates that an entity is expressed, encoded, or represented using a particular natural or formal language.
-
E.
hasLinguisticElement
Indicates that one entity includes, is associated with, or is characterized by a particular linguistic component such as a word, phrase, symbol, or other language element.
- 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_69e77e8046888190b07ffa58c7e2c37a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f6bbf6e33c819086e5176d64e7a614 |
completed | May 3, 2026, 3:07 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6b1e6c8190adf9d6a257e0b744 |
completed | May 3, 2026, 3 a.m. |
Created at: April 21, 2026, 8:13 p.m.