Triple
T35920626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winter (from the Four Seasons) |
E1038871
|
entity |
| Predicate | hasDepictionOfClothing |
P174781
|
FINISHED |
| Object | warm winter garments |
—
|
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: warm winter garments | Statement: [Winter (from the Four Seasons), hasDepictionOfClothing, warm winter garments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDepictionOfClothing Context triple: [Winter (from the Four Seasons), hasDepictionOfClothing, warm winter garments]
-
A.
oftenDepictedWearing
Indicates that an entity is frequently shown or represented as wearing a particular item or type of clothing in depictions or portrayals.
-
B.
hasGarment
Indicates that one entity possesses, wears, or is associated with a particular garment.
-
C.
showsClothing
chosen
Indicates that one entity visually presents or displays an item of clothing associated with another entity.
-
D.
hasClothingSource
Indicates that an entity’s clothing originates from, is supplied by, or is obtained through a specified source.
-
E.
depictedItem
Indicates that one entity visually represents or portrays another entity in some form of depiction.
- 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_69f76e2320748190b7f5c4750d0cd0d3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff5b233e9c8190adc06cca0758986b |
completed | May 9, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69ff5a5682108190a006b23c4fcdcc7c |
completed | May 9, 2026, 4:01 p.m. |
Created at: May 3, 2026, 4:07 p.m.