Triple
T26235958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Australian Gallantry Decorations |
E656165
|
entity |
| Predicate | ribbonWornWith |
P30718
|
FINISHED |
| Object | distinctive ribbon for each grade |
—
|
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: distinctive ribbon for each grade | Statement: [Australian Gallantry Decorations, ribbonWornWith, distinctive ribbon for each grade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ribbonWornWith Context triple: [Australian Gallantry Decorations, ribbonWornWith, distinctive ribbon for each grade]
-
A.
ribbonType
chosen
Indicates the specific kind or category of ribbon associated with an entity.
-
B.
wornAround
Indicates that one entity is physically worn encircling or surrounding another entity (e.g., around a body part or object).
-
C.
wearsRibbonOf
Indicates that one entity is adorned with or has attached to it a ribbon associated with another entity.
-
D.
beltType
Indicates the specific kind or category of belt associated with an entity.
-
E.
typeOfTie
Indicates the specific kind or category of relationship or connection that exists between two entities.
- 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_69ee5b4b8b408190993da38c0067cc8d |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f60d8ab3b481908e7feeda0f8c47fa |
completed | May 2, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69f5f7fd90fc81909055b211368f9139 |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 26, 2026, 9:01 p.m.