Triple
T22841861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commander by Number of the Order of Isabella the Catholic |
E566101
|
entity |
| Predicate | hasDecorationForm |
P2788
|
FINISHED |
| Object | neck badge |
—
|
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: neck badge | Statement: [Commander by Number of the Order of Isabella the Catholic, hasDecorationForm, neck badge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDecorationForm Context triple: [Commander by Number of the Order of Isabella the Catholic, hasDecorationForm, neck badge]
-
A.
hasDecor
Indicates that one entity possesses, features, or is adorned with a particular decorative element or style.
-
B.
containsDecorationFrom
Indicates that one entity includes or incorporates a decorative element that originates from another entity.
-
C.
decorationForm
Indicates the specific decorative style, pattern, or motif that characterizes how something is ornamented.
-
D.
isStateDecoration
Indicates that an item is an official decoration or honor conferred by a state or government authority.
-
E.
typeOfDecoration
chosen
Indicates the specific kind or style of decoration associated with an entity or applied in a given context.
- 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_69e245869e188190a196584f36e682da |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e855abc8190b9cf8cc515090a7f |
completed | April 29, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69eed2d117088190acbfe130d84f8627 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:35 p.m.