Triple
T191026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Officier de la Légion d'honneur |
E3720
|
entity |
| Predicate | higherGrade |
P3584
|
FINISHED |
| Object | Commandeur de la Légion d'honneur |
—
|
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: Commandeur de la Légion d'honneur | Statement: [Officier de la Légion d'honneur, higherGrade, Commandeur de la Légion d'honneur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: higherGrade Context triple: [Officier de la Légion d'honneur, higherGrade, Commandeur de la Légion d'honneur]
-
A.
higherAward
Indicates that one entity has received an award that is of greater prestige, rank, or value than the award received by another entity.
-
B.
nextHigherRank
chosen
Indicates that one entity holds the immediately superior rank or level in a hierarchy relative to another entity.
-
C.
hasHigherClass
Indicates that one entity belongs to a higher rank, level, or category in a hierarchy than another entity.
-
D.
above
Indicates that one entity is positioned higher than another along a vertical axis, without implying direct contact.
-
E.
orderGradeLevel
Indicates the relative sequencing or ranking of grade levels, specifying which grade comes before or after another.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a25964fc5c8190bd3e37daaf695ecf |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a25673ce3c8190b1a3df5b814a0595 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.