Triple
T6634692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Officer of the National Order of Merit (France) |
E150417
|
entity |
| Predicate | gradeLevelInOrder |
P2799
|
FINISHED |
| Object | second grade above Knight |
—
|
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: second grade above Knight | Statement: [Officer of the National Order of Merit (France), gradeLevelInOrder, second grade above Knight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gradeLevelInOrder Context triple: [Officer of the National Order of Merit (France), gradeLevelInOrder, second grade above Knight]
-
A.
orderGradeLevel
chosen
Indicates the relative sequencing or ranking of grade levels, specifying which grade comes before or after another.
-
B.
denotesGradeLevel
Indicates that one entity specifies or assigns the educational grade level associated with another entity.
-
C.
gradeName
Indicates the specific name or label assigned to a grade level associated with an entity.
-
D.
gradeWithin
Indicates that one value’s grade or level falls within a specified range or interval relative to another.
-
E.
gradeRange
Indicates the span of grades or scores that an item, performance, or entity falls within.
- 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_69c687f0ceb08190bf40807bfc605fa5 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c308a08881908501c862b3029321 |
completed | March 27, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c6ad024860819084b9b535b136ede6 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:59 p.m.