Triple
T57520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commander of the Order of Arts and Letters of France |
E1137
|
entity |
| Predicate | orderHasThreeGrades |
P2814
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Commander of the Order of Arts and Letters of France, orderHasThreeGrades, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orderHasThreeGrades Context triple: [Commander of the Order of Arts and Letters of France, orderHasThreeGrades, true]
-
A.
hasGrades
Indicates that an entity possesses or is associated with one or more grade values, typically reflecting evaluations or scores.
-
B.
hasOrder
Indicates that one entity possesses, is associated with, or is characterized by a specific order, sequence, or arrangement relative to others.
-
C.
isGradeOf
Indicates that one entity is the grade or evaluation assigned to another entity, such as a student, assignment, or performance.
-
D.
orderType
Indicates the specific category or classification of an order, such as its purpose, channel, or processing method.
-
E.
hasDivisionLevel
Indicates that one entity is associated with a specific hierarchical or organizational division level of another entity.
- F. None of above. chosen
Provenance (4 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24b915c9881908c798f4dacb39f1d |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24ac6799c8190b508933acc0a4c7d |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24b90ab24819085478dbe95f717dd |
completed | Feb. 28, 2026, 1:57 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.