Triple
T327295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Officier de la Légion d'honneur |
E6546
|
entity |
| Predicate | belongsToAwardSystem |
P219
|
FINISHED |
| Object | French national honors system |
—
|
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: French national honors system | Statement: [Grand Officier de la Légion d'honneur, belongsToAwardSystem, French national honors system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToAwardSystem Context triple: [Grand Officier de la Légion d'honneur, belongsToAwardSystem, French national honors system]
-
A.
canBeAwardedTo
Indicates that something is eligible to receive or be granted a particular award, honor, or recognition.
-
B.
awardsQualificationTo
Indicates that one entity grants or confers a qualification, certification, or credential to another entity.
-
C.
relatedAward
chosen
Indicates that there is an award connected or associated with the subject entity, such as an honor, prize, or recognition related to it.
-
D.
hasAwarded
Indicates that one entity has given or conferred an award to another entity.
-
E.
hasAwardingBodyType
Indicates that an entity has an associated type or category describing the kind of organization or body that grants an award.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea98fa2c8190a5b44f4a26543a17 |
completed | Feb. 28, 2026, 1:16 p.m. |
| PD | Predicate disambiguation | batch_69a2e94aab1c8190b8654708c87eeb91 |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.