Triple
T8314054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muslim conquest of North Africa |
E194658
|
entity |
| Predicate | preExistingLanguage |
P28976
|
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: [Muslim conquest of North Africa, preExistingLanguage, Latin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: preExistingLanguage Context triple: [Muslim conquest of North Africa, preExistingLanguage, Latin]
-
A.
coexistsWithLanguage
Indicates that one entity exists or functions alongside a particular language at the same time, without excluding or replacing it.
-
B.
primaryReplacementLanguage
Indicates that one language serves as the main or preferred substitute for another language when the original cannot be used.
-
C.
preservesLanguage
Indicates that an entity actively maintains, protects, or continues the use of a particular language so it does not decline or disappear.
-
D.
eligibleLanguage
Indicates that a particular language satisfies the required conditions to be considered valid or allowed in a given context.
-
E.
formerLanguage
chosen
Indicates that one entity was previously the language of another entity but is no longer in that role.
- 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_69ca82e6e2648190a31eaf6f4f757b2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f52c5cc8190b5a95ee0aa4ddda5 |
completed | March 31, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69cb70bf689c8190a9d9b6b872abf53d |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:55 p.m.