Triple
T29959715
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cold Shoulder |
E761006
|
entity |
| Predicate | stylingUse |
P64230
|
FINISHED |
| Object | to show skin while maintaining coverage |
—
|
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: to show skin while maintaining coverage | Statement: [Cold Shoulder, stylingUse, to show skin while maintaining coverage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stylingUse Context triple: [Cold Shoulder, stylingUse, to show skin while maintaining coverage]
-
A.
usedWithStyle
Indicates that something is employed or applied in conjunction with a particular style or stylistic manner.
-
B.
usesMakeupStyle
Indicates that one entity applies or adopts the makeup style or technique associated with another entity.
-
C.
usedStyle
chosen
Indicates that one entity employed or applied a particular style, method, or manner associated with another entity.
-
D.
stylingEnables
Indicates that one entity provides or activates styling capabilities or visual formatting for another entity.
-
E.
styleTendsTo
Indicates that one style is generally inclined or likely to develop, appear, or be adopted in the direction of another style.
- 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_69f22466327481908ba6db916837bece |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6783d1944819080f26d4d2fdd1256 |
completed | May 2, 2026, 10:18 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:28 p.m.