Triple
T29095269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Panther blue jersey |
E734978
|
entity |
| Predicate | clothingCategory |
P160564
|
FINISHED |
| Object | athletic apparel |
—
|
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: athletic apparel | Statement: [Panther blue jersey, clothingCategory, athletic apparel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: clothingCategory Context triple: [Panther blue jersey, clothingCategory, athletic apparel]
-
A.
fashionCategory
chosen
Indicates the classification of an item into a specific fashion-related category or type (e.g., clothing, footwear, accessories).
-
B.
garmentType
Indicates the specific kind or category of garment associated with an entity.
-
C.
clothingPurpose
Indicates the functional role or intended use that a particular item of clothing serves (e.g., protection, fashion, uniform, sport).
-
D.
colorOfApparel
Indicates the specific color attribute associated with a piece of apparel or clothing item.
-
E.
bodyStyleCategory
Indicates the general body style classification or category that an item (such as a vehicle or product) belongs to.
- 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_69f05b0ed66481908f2e864fa550d2f1 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f6618069888190aa87dd09a751a2c2 |
completed | May 2, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f65c2376a08190be5215171e908e69 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 11:08 a.m.