Triple
T38488852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kasanga language |
E917995
|
entity |
| Predicate | hasFeatureTypicalOf |
P29386
|
FINISHED |
| Object | Southern Gur languages |
—
|
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: Southern Gur languages | Statement: [Kasanga language, hasFeatureTypicalOf, Southern Gur languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFeatureTypicalOf Context triple: [Kasanga language, hasFeatureTypicalOf, Southern Gur languages]
-
A.
typicalFeatures
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
-
B.
hasFeature
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
-
C.
isFeatureOf
chosen
Indicates that something functions as a characteristic, attribute, or component belonging to or describing another entity.
-
D.
hasPrimaryFeature
Indicates that an entity possesses a main or most characteristic feature that defines or distinguishes it.
-
E.
isFeatureBased
Indicates that one entity is derived from, determined by, or constructed using the characteristics or attributes of another entity.
- 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_69f76e9894208190a129a553a60ca58c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fd3d46d1f48190a1b20dd063224b7d |
completed | May 8, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69fd3ae1510c81908fe1280efc17feee |
completed | May 8, 2026, 1:22 a.m. |
Created at: May 3, 2026, 4:31 p.m.