Triple
T25427940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hiljainen kansa |
E637166
|
entity |
| Predicate | hasClothingSource |
P162098
|
FINISHED |
| Object | donated clothes |
—
|
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: donated clothes | Statement: [Hiljainen kansa, hasClothingSource, donated clothes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClothingSource Context triple: [Hiljainen kansa, hasClothingSource, donated clothes]
-
A.
hasGarment
Indicates that one entity possesses, wears, or is associated with a particular garment.
-
B.
usesDressing
Indicates that one entity applies or employs a particular dressing (such as a sauce, covering, or treatment) in relation to another entity or context.
-
C.
clothingFeature
Indicates that one entity has a specific clothing-related attribute, detail, or characteristic associated with it.
-
D.
mayBeWorn
Indicates that one entity is suitable or allowed to be worn by another entity, typically as clothing, accessories, or adornment.
-
E.
garmentType
Indicates the specific kind or category of garment associated with an entity.
- F. None of above. chosen
Provenance (4 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_69e75db58a1c8190891b9ff7c2f8414e |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f622abdfac8190988421c946411d7e |
completed | May 2, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69f621fbfc2c8190bfa802d7dc0f6aa4 |
completed | May 2, 2026, 4:10 p.m. |
Created at: April 21, 2026, 1:57 p.m.