Triple
T29351923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Military Merit Medal (Signum Laudis) |
E744335
|
entity |
| Predicate | ribbonVariant |
P30718
|
FINISHED |
| Object | war decoration ribbon with laurel wreath |
—
|
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: war decoration ribbon with laurel wreath | Statement: [Military Merit Medal (Signum Laudis), ribbonVariant, war decoration ribbon with laurel wreath]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ribbonVariant Context triple: [Military Merit Medal (Signum Laudis), ribbonVariant, war decoration ribbon with laurel wreath]
-
A.
ribbonType
chosen
Indicates the specific kind or category of ribbon associated with an entity.
-
B.
ribbonName
Indicates the specific name or label assigned to a ribbon within a system or context.
-
C.
ribbonDesignFeature
Indicates a design-related characteristic or attribute that is specifically associated with a ribbon.
-
D.
ribbonInscription
Indicates that a ribbon bears or displays a particular inscription or text.
-
E.
ribbonRepresents
Indicates that a ribbon symbolically stands for, signifies, or is used to represent something (such as a cause, concept, or affiliation).
- 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_69f0a79a2d748190bc30abd469298b37 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f6695baebc81909cc09eaddd4290a7 |
completed | May 2, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69f660f4f7a88190b93c60d76b86c912 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 28, 2026, 2:07 p.m.