Triple
T11151224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Misha |
E263789
|
entity |
| Predicate | hasClothingItem |
P42160
|
FINISHED |
| Object | belt |
—
|
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: belt | Statement: [Misha, hasClothingItem, belt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClothingItem Context triple: [Misha, hasClothingItem, belt]
-
A.
hasGarment
chosen
Indicates that one entity possesses, wears, or is associated with a particular garment.
-
B.
mayBeWorn
Indicates that one entity is suitable or allowed to be worn by another entity, typically as clothing, accessories, or adornment.
-
C.
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.
-
D.
coatCharacteristic
Indicates that one entity has a particular property, feature, or quality that characterizes its outer covering or surface.
-
E.
typicallyWornWith
Indicates that one item of clothing or accessory is commonly or customarily worn together with another.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8719e74819095413abc6c79296c |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75ce71944819089eee9b5c9283cbd |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.