Triple
T16293003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Cross of the Military Order of William |
E395571
|
entity |
| Predicate | badgeMaterial |
P122557
|
FINISHED |
| Object | gold |
—
|
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: gold | Statement: [Grand Cross of the Military Order of William, badgeMaterial, gold]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: badgeMaterial Context triple: [Grand Cross of the Military Order of William, badgeMaterial, gold]
-
A.
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.
-
B.
badgeText
Indicates that a visual badge or label is associated with an entity, displaying specific text content.
-
C.
badgeVariesBy
Indicates that the characteristics or appearance of a badge change depending on some varying condition, context, or parameter.
-
D.
badgeCategory
Indicates the classification or type group to which a particular badge belongs.
-
E.
badgeEnamelColor
Indicates the color of the enamel portion of a badge.
- F. None of above. chosen
Provenance (4 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e2aee6881909fd28547f135427c |
completed | April 17, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69e219f68d308190b71c1601303f0628 |
completed | April 17, 2026, 11:31 a.m. |
| PDg | Predicate description generation | batch_69e21e56e0348190a3d9475360231a70 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:05 a.m.