Triple
T2006339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Islamization of North Africa |
E43594
|
entity |
| Predicate | languageDiminished |
P4292
|
FINISHED |
| Object | Latin |
—
|
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: Latin | Statement: [Islamization of North Africa, languageDiminished, Latin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageDiminished Context triple: [Islamization of North Africa, languageDiminished, Latin]
-
A.
languageShift
chosen
Indicates a change in the primary language used by an entity, such as switching from one language to another over time or in a given context.
-
B.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
C.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
-
D.
languageCapacity
Indicates the extent to which an entity is able to understand, produce, or otherwise use language.
-
E.
languageForm
Indicates the specific linguistic form or expression in which something is conveyed or represented.
- 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_69a88715dbbc8190b2299e29e955d997 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb898795481909920c1a4c4d62c2d |
completed | March 7, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69abb79e63c08190982c8b44a557266f |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:37 p.m.