Triple
T31688126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French in Morocco |
E808715
|
entity |
| Predicate | mainDomainsOfUse |
P24492
|
FINISHED |
| Object | education |
—
|
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: education | Statement: [French in Morocco, mainDomainsOfUse, education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainDomainsOfUse Context triple: [French in Morocco, mainDomainsOfUse, education]
-
A.
primaryUseOf
Indicates that one entity serves as the main or principal function, purpose, or application of another entity.
-
B.
mainlyUses
Indicates that one entity primarily relies on, employs, or utilizes another entity as its main tool, method, resource, or medium.
-
C.
publicDomain
Indicates that a work or resource is not protected by intellectual property rights and is freely available for anyone to use, copy, modify, and distribute without restriction.
-
D.
typicalDomain
chosen
Indicates that one entity is the characteristic or most common domain, context, or area of application in which another entity typically occurs or is used.
-
E.
usedInDomain
Indicates that something (such as a concept, method, or resource) is applied or utilized within a particular domain or field.
- 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_69f348ddcbc48190950cabcc25ff29b3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6aaf50be08190a2b62a6d881f8aee |
completed | May 3, 2026, 1:55 a.m. |
| PD | Predicate disambiguation | batch_69f6aa20a1588190a53533fc9764efb2 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 11:07 p.m.