Triple
T28796792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coordination of Azawad Movements |
E727105
|
entity |
| Predicate | languageUsedInternally |
P58450
|
FINISHED |
| Object | Tamasheq |
—
|
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: Tamasheq | Statement: [Coordination of Azawad Movements, languageUsedInternally, Tamasheq]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedInternally Context triple: [Coordination of Azawad Movements, languageUsedInternally, Tamasheq]
-
A.
languagesUsed
chosen
Indicates that one entity uses, employs, or is expressed in one or more languages associated with the other entity.
-
B.
languageOfImplementation
Indicates the programming language in which a given software system, component, or algorithm is implemented.
-
C.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
D.
languageOfCode
Indicates that a programming code artifact is written in, or uses, a particular programming language.
-
E.
alsoUsedLanguageInProgramming
Indicates that an entity used an additional programming language, beyond a primary one, in the context of programming.
- 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_69f0319b7c44819085736bcc256185e6 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69fe349879848190bcd77e3cc3470458 |
completed | May 8, 2026, 7:08 p.m. |
| PD | Predicate disambiguation | batch_69fe31e3cf908190b23ebc2f7fe58722 |
completed | May 8, 2026, 6:56 p.m. |
Created at: April 28, 2026, 6:25 a.m.