Triple
T9339501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monsieur le Garde des Sceaux |
E224727
|
entity |
| Predicate | titleRelatesTo |
P5175
|
FINISHED |
| Object | French justice system |
—
|
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: French justice system | Statement: [Monsieur le Garde des Sceaux, titleRelatesTo, French justice system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleRelatesTo Context triple: [Monsieur le Garde des Sceaux, titleRelatesTo, French justice system]
-
A.
titleRelation
Indicates a relationship where one entity serves as the title, designation, or formal name associated with another entity.
-
B.
relatedTitleHolder
Indicates that one entity holds a title or position that is related or connected to the title or position held by another entity.
-
C.
associatedTitle
chosen
Indicates that one entity has a title, designation, or formal label that is linked or relevant to another entity.
-
D.
titleHolderRelationship
Indicates a relationship where one entity holds, possesses, or bears a specific title in connection to another entity or context.
-
E.
titleAlludesTo
Indicates that one title makes an indirect or suggestive reference to the content, theme, or another work associated with the other.
- 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_69ca84286fcc81909f6e7fd7a7e862a2 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4bace8488190a18c54e03be8410c |
completed | April 1, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69cc7a66aef08190b8d668cff5b04f5f |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:40 p.m.