Triple
T1260808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allow Me |
E12494
|
entity |
| Predicate | subjectDress |
P15063
|
FINISHED |
| Object | business suit |
—
|
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: business suit | Statement: [Allow Me, subjectDress, business suit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectDress Context triple: [Allow Me, subjectDress, business suit]
-
A.
garmentType
chosen
Indicates the specific kind or category of garment associated with an entity.
-
B.
wardrobeFeature
Indicates that a wardrobe possesses or includes a specific feature, attribute, or functional element.
-
C.
nationalDress
Indicates that an item of clothing is recognized as the traditional or customary dress associated with a particular nation or culture.
-
D.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfc64e648190b9c4f980eb8168aa |
completed | March 1, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6eefbc81908dddd7d2ef368186 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:50 p.m.