Triple
T18681880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | coronation mantle of Hungary |
E456751
|
entity |
| Predicate | typeOfClothing |
P15063
|
FINISHED |
| Object | liturgical vestment |
—
|
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: liturgical vestment | Statement: [coronation mantle of Hungary, typeOfClothing, liturgical vestment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfClothing Context triple: [coronation mantle of Hungary, typeOfClothing, liturgical vestment]
-
A.
garmentType
chosen
Indicates the specific kind or category of garment associated with an entity.
-
B.
coatCharacteristic
Indicates that one entity has a particular property, feature, or quality that characterizes its outer covering or surface.
-
C.
colorOfApparel
Indicates the specific color attribute associated with a piece of apparel or clothing item.
-
D.
hasGarment
Indicates that one entity possesses, wears, or is associated with a particular garment.
-
E.
dressRecommendation
Indicates a suggested or advised choice of dress for a particular person and/or occasion.
- 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e55b2906ec8190ad8db8e3ae6b2945 |
completed | April 19, 2026, 10:46 p.m. |
| PD | Predicate disambiguation | batch_69e478db7a248190a8c6584673773923 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:49 a.m.