Triple
T34153046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iraqw people |
E876054
|
entity |
| Predicate | useOfSwahili |
P108903
|
FINISHED |
| Object | widespread as lingua franca |
—
|
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: widespread as lingua franca | Statement: [Iraqw people, useOfSwahili, widespread as lingua franca]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: useOfSwahili Context triple: [Iraqw people, useOfSwahili, widespread as lingua franca]
-
A.
usesKunya
Indicates that one entity refers to or identifies another entity by a kunya (a teknonymic nickname, typically based on "father/mother of" someone).
-
B.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
-
C.
usedForLanguageSpokenIn
Indicates that something (such as a resource, tool, or medium) is used for expressing or communicating a language that is spoken in a particular place or region.
-
D.
usesLanguageFor
chosen
Indicates that an entity employs a particular language as a tool or medium to perform some activity, function, or purpose.
-
E.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with 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_69f349abaa508190a820f206620efddc |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70fb4f18c819099ef6d9177b7d205 |
completed | May 3, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f70f3a54d481909ba6bdda3647b761 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:54 a.m.