Triple
T327288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Officier de la Légion d'honneur |
E6546
|
entity |
| Predicate | typeOfMerit |
P1619
|
FINISHED |
| Object | national merit |
—
|
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: national merit | Statement: [Grand Officier de la Légion d'honneur, typeOfMerit, national merit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfMerit Context triple: [Grand Officier de la Légion d'honneur, typeOfMerit, national merit]
-
A.
honourType
Indicates the specific category or classification of an honour or award associated with an entity.
-
B.
awardCriteria
Indicates the standards or conditions used to determine eligibility for receiving an award or recognition.
-
C.
awardFor
Indicates that something is given or granted as recognition or a prize for a particular achievement, work, or contribution.
-
D.
prizeType
Indicates the specific category or kind of prize associated with an entity or event.
-
E.
awardType
chosen
Indicates the specific category or kind of award associated with an entity or event.
- 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.