Triple
T24175533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ngoni people |
E599271
|
entity |
| Predicate | shareLinguisticTraitsWith |
P114100
|
FINISHED |
| Object | Zulu language |
—
|
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: Zulu language | Statement: [Ngoni people, shareLinguisticTraitsWith, Zulu language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shareLinguisticTraitsWith Context triple: [Ngoni people, shareLinguisticTraitsWith, Zulu language]
-
A.
sharesLinguisticFamilyWith
Indicates that two languages belong to the same linguistic family or branch within a language family.
-
B.
hasDialectalFeaturesSharedWith
chosen
Indicates that two language varieties share specific dialectal features or characteristics in common.
-
C.
sharesLanguageWith
Indicates that two entities use at least one common language for communication.
-
D.
shareLanguageInfluence
Indicates that two entities affect or shape each other’s language use, development, or characteristics through mutual or shared influence.
-
E.
shareLanguageFamilyContext
Indicates that two entities are associated with languages that belong to the same language family or broader linguistic grouping within a given context.
- 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_69e288cca05481908faeb1563711114a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9ddfcc819096697a844b300cce |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:34 p.m.