Triple
T19752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chevalier de la Légion d'honneur |
E393
|
entity |
| Predicate | gradeLevel |
P337
|
FINISHED |
| Object | 5th class |
—
|
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: 5th class | Statement: [Chevalier de la Légion d'honneur, gradeLevel, 5th class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gradeLevel Context triple: [Chevalier de la Légion d'honneur, gradeLevel, 5th class]
-
A.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
B.
educatedAt
Indicates that an entity received education or formal training at a specified institution or place of learning.
-
C.
academicDegree
Indicates that an entity holds or has been awarded a specific academic degree.
-
D.
primaryLanguageOfInstruction
Indicates the language that is mainly used as the medium of teaching or instruction for a given educational context.
-
E.
honorLevel
chosen
Indicates the degree or status of respect, distinction, or recognition accorded to an entity relative to others.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a24703cb988190ad2bc181d27829e4 |
completed | Feb. 28, 2026, 1:38 a.m. |
| PD | Predicate disambiguation | batch_69a24650f1f0819081e638fafd18d687 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.