Triple
T11068418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Islam in Yemen |
E261682
|
entity |
| Predicate | influencesDressCode |
P2738
|
FINISHED |
| Object | modest Islamic dress in Yemen |
—
|
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: modest Islamic dress in Yemen | Statement: [Islam in Yemen, influencesDressCode, modest Islamic dress in Yemen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencesDressCode Context triple: [Islam in Yemen, influencesDressCode, modest Islamic dress in Yemen]
-
A.
hasDressCode
chosen
Indicates that a specified entity enforces or is associated with a particular set of rules governing appropriate clothing or attire.
-
B.
designInfluenceOn
Indicates that one design, designer, or design-related factor has an effect on shaping, guiding, or altering another design or design outcome.
-
C.
usualAttire
Indicates the type of clothing an entity typically wears in ordinary or characteristic situations.
-
D.
fashionStyle
Indicates the characteristic way in which an entity dresses or presents themselves in terms of clothing and appearance.
-
E.
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.
- 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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7992164d88190a01ed567b2529227 |
completed | April 9, 2026, 12:18 p.m. |
| PD | Predicate disambiguation | batch_69d74411d9e881908c0eeafa0f38e4b6 |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:26 p.m.