Triple
T548939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Standard of the Prime Minister of France |
E12795
|
entity |
| Predicate | typeOfSymbol |
P4224
|
FINISHED |
| Object | state symbol of 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: state symbol of France | Statement: [Standard of the Prime Minister of France, typeOfSymbol, state symbol of France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfSymbol Context triple: [Standard of the Prime Minister of France, typeOfSymbol, state symbol of France]
-
A.
symbolType
Indicates the classification or category of a symbol based on its role, form, or function within a given system.
-
B.
typeOf
chosen
Indicates that one entity is a specific kind, class, or category instance of another more general entity.
-
C.
typeOfAnnotation
Indicates that one entity is an annotation and specifies the kind or category of that annotation in relation to the annotated item.
-
D.
invariantType
Indicates that one entity has a type or classification that remains constant or unchanged under specified conditions or transformations.
-
E.
semanticType
Indicates that something belongs to or is categorized under a particular semantic class or type based on its meaning.
- 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_69a49334226c81908b0ea1689ef6aa3f |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49900895c819092a131c185a758bf |
completed | March 1, 2026, 7:52 p.m. |
| PD | Predicate disambiguation | batch_69a494bae210819093c2e0d33a8ca51a |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.