Triple
T30470437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Elizabeth II portrait (2007) |
E775276
|
entity |
| Predicate | portraysClothingType |
P128303
|
FINISHED |
| Object | royal regalia |
—
|
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 regalia | Statement: [Queen Elizabeth II portrait (2007), portraysClothingType, royal regalia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysClothingType Context triple: [Queen Elizabeth II portrait (2007), portraysClothingType, royal regalia]
-
A.
oftenDepictedWearing
chosen
Indicates that an entity is frequently shown or represented as wearing a particular item or type of clothing in depictions or portrayals.
-
B.
garmentType
Indicates the specific kind or category of garment associated with an entity.
-
C.
showsClothing
Indicates that one entity visually presents or displays an item of clothing associated with another entity.
-
D.
coatCharacteristic
Indicates that one entity has a particular property, feature, or quality that characterizes its outer covering or surface.
-
E.
portraysProduct
Indicates that one entity visually or narratively represents, depicts, or features a particular product.
- 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_69f2249622a48190b1fae2e3e4ee958a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd6f9d600c8190acf495b7fc632e4b |
completed | May 8, 2026, 5:07 a.m. |
| PD | Predicate disambiguation | batch_69fd6e98a2948190a9f78c415ad23b8c |
completed | May 8, 2026, 5:03 a.m. |
Created at: April 29, 2026, 8:11 p.m.