Triple
T18767410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Officer of the Order of the Crown (Belgium) |
E458926
|
entity |
| Predicate | badgeCentralMotive |
P51203
|
FINISHED |
| Object | royal crown of Belgium |
—
|
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: royal crown of Belgium | Statement: [Grand Officer of the Order of the Crown (Belgium), badgeCentralMotive, royal crown of Belgium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: badgeCentralMotive Context triple: [Grand Officer of the Order of the Crown (Belgium), badgeCentralMotive, royal crown of Belgium]
-
A.
badgeCentralMotif
chosen
Indicates that one entity serves as the central or primary motif featured on a badge in relation to another entity.
-
B.
badge
Indicates that one entity confers, displays, or is associated with a symbolic mark or emblem representing status, achievement, role, or affiliation in relation to another entity.
-
C.
badgeCategory
Indicates the classification or type group to which a particular badge belongs.
-
D.
badgeVariesBy
Indicates that the characteristics or appearance of a badge change depending on some varying condition, context, or parameter.
-
E.
badgeMaterial
Indicates the material from which a badge is made.
- 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_69d8d395dba0819087568404508590cb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e58d859c8081909cec3aa64d264885 |
completed | April 20, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69e48d0b7b708190877951b6e6cdcbc4 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:52 a.m.