Triple
T6634679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Officer of the National Order of Merit (France) |
E150417
|
entity |
| Predicate | orderHasGrade |
P1863
|
FINISHED |
| Object | Officer |
—
|
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: Officer | Statement: [Officer of the National Order of Merit (France), orderHasGrade, Officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orderHasGrade Context triple: [Officer of the National Order of Merit (France), orderHasGrade, Officer]
-
A.
hasGradeWithinOrder
Indicates that one entity’s grade or rank falls within a specified ordered range or position relative to another entity.
-
B.
orderHasThreeGrades
Indicates that an order is associated with exactly three distinct grades or levels.
-
C.
hasGradeCount
Indicates a relationship where an entity is associated with the number of grades it has or has received.
-
D.
orderGradeLevel
Indicates the relative sequencing or ranking of grade levels, specifying which grade comes before or after another.
-
E.
hasGrades
chosen
Indicates that an entity possesses or is associated with one or more grade values, typically reflecting evaluations or scores.
- 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.