Triple
T3115919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Ministry of Higher Education and Research |
E65061
|
entity |
| Predicate | implementsPolicyFor |
P172
|
FINISHED |
| Object | higher education in France |
—
|
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: higher education in France | Statement: [French Ministry of Higher Education and Research, implementsPolicyFor, higher education in France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: implementsPolicyFor Context triple: [French Ministry of Higher Education and Research, implementsPolicyFor, higher education in France]
-
A.
implementedPolicy
chosen
Indicates that a particular policy has been put into effect or carried out by an entity.
-
B.
supportsPolicy
Indicates that one entity endorses, backs, or is in favor of a particular policy or set of policies.
-
C.
usesPolicyModel
Indicates that one entity applies, relies on, or operates according to a particular policy model.
-
D.
declaredPolicy
Indicates that an entity has formally stated or announced a specific policy or course of action.
-
E.
issuesPolicyOn
Indicates that an authority or organization formally creates, approves, or enacts a policy concerning a particular subject or domain.
- 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_69ad857fcc088190b0c4d45a5cde6f61 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada4e40bc48190b9b17c706a2450d5 |
completed | March 8, 2026, 4:33 p.m. |
| PD | Predicate disambiguation | batch_69ad9df455088190940ad04419772dc8 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:04 p.m.