Triple
T191027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Officier de la Légion d'honneur |
E3720
|
entity |
| Predicate | lowerGrade |
P2799
|
FINISHED |
| Object | Chevalier 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: Chevalier de la Légion d'honneur | Statement: [Officier de la Légion d'honneur, lowerGrade, Chevalier de la Légion d'honneur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lowerGrade Context triple: [Officier de la Légion d'honneur, lowerGrade, Chevalier de la Légion d'honneur]
-
A.
orderGradeLevel
chosen
Indicates the relative sequencing or ranking of grade levels, specifying which grade comes before or after another.
-
B.
servesGradeLevels
Indicates that an entity (such as a school or program) provides services or instruction to students in the specified grade levels.
-
C.
lowerHouse
Indicates that one entity functions as the lower chamber of a bicameral legislature in relation to a given political body or system.
-
D.
hasLower
Indicates that one entity is positioned at a lower level, rank, or value relative to another entity.
-
E.
lowestPoint
Indicates that one entity is the point with the minimum vertical position or value relative to another entity or within a specified context.
- 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.