Triple
T25175928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malawi and Mozambique |
E630445
|
entity |
| Predicate | shareLanguagesFamilyContext |
P85377
|
FINISHED |
| Object | Bantu languages widely spoken |
—
|
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: Bantu languages widely spoken | Statement: [Malawi and Mozambique, shareLanguagesFamilyContext, Bantu languages widely spoken]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shareLanguagesFamilyContext Context triple: [Malawi and Mozambique, shareLanguagesFamilyContext, Bantu languages widely spoken]
-
A.
shareLanguageFamilyContext
chosen
Indicates that two entities are associated with languages that belong to the same language family or broader linguistic grouping within a given context.
-
B.
languageOfFamily
Indicates the language or languages commonly used or associated with a particular family.
-
C.
languageFamilyAssociated
Indicates that there is an association or connection between a language and a particular language family.
-
D.
languageFamily
Indicates that two or more languages belong to the same genealogical language family or linguistic lineage.
-
E.
coversLanguageFamily
Indicates that one entity includes or encompasses a particular language family within its scope or subject matter.
- 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_69e75a88fdf081908e47ae6e195c14e1 |
completed | April 21, 2026, 11:07 a.m. |
| NER | Named-entity recognition | batch_69f6a8df16a88190a23820e64a3b1f92 |
completed | May 3, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69f6a751d5e48190a77dcecbe7ef9f0b |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 21, 2026, 12:34 p.m.