Triple
T12916164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ciluba |
E308987
|
entity |
| Predicate | hasNounClassCount |
P106995
|
FINISHED |
| Object | over 10 grammatical noun classes |
—
|
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: over 10 grammatical noun classes | Statement: [Ciluba, hasNounClassCount, over 10 grammatical noun classes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNounClassCount Context triple: [Ciluba, hasNounClassCount, over 10 grammatical noun classes]
-
A.
hasNounClassSystem
Indicates that an entity possesses a grammatical system in which nouns are categorized into distinct classes that affect their agreement with other elements in the language.
-
B.
hasNoun
Indicates that an entity possesses or is associated with a specific noun as an attribute, label, or grammatical component.
-
C.
hasGrammaticalNumber
Indicates that an expression is associated with a specific grammatical number category (such as singular, plural, or dual) in a language.
-
D.
hasNounDeclensionType
Indicates that a noun is associated with a specific grammatical declension pattern or type.
-
E.
hasNounEnding
Indicates that something possesses or exhibits a particular noun-forming ending or suffix.
- F. None of above. chosen
Provenance (4 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971a1e8088190af697629baecf59f |
completed | April 10, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69d96fa9b7708190a9e9fa30f59ff580 |
completed | April 10, 2026, 9:46 p.m. |
| PDg | Predicate description generation | batch_69d9708a86bc8190bcdcf97e845bb413 |
completed | April 10, 2026, 9:50 p.m. |
Created at: April 9, 2026, 5:41 p.m.