Triple
T6377638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Islamic Emirate of Afghanistan |
E143503
|
entity |
| Predicate | implementsDressCode |
P2738
|
FINISHED |
| Object | strict dress code for women |
—
|
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: strict dress code for women | Statement: [Islamic Emirate of Afghanistan, implementsDressCode, strict dress code for women]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: implementsDressCode Context triple: [Islamic Emirate of Afghanistan, implementsDressCode, strict dress code for women]
-
A.
hasDressCode
chosen
Indicates that a specified entity enforces or is associated with a particular set of rules governing appropriate clothing or attire.
-
B.
usualAttire
Indicates the type of clothing an entity typically wears in ordinary or characteristic situations.
-
C.
ceremonialDressFeature
Indicates that one entity is a characteristic, component, or distinguishing element of another entity’s ceremonial dress or attire.
-
D.
isCostumed
Indicates that an entity is wearing or otherwise adorned with a costume.
-
E.
hasTraditionalAttire
Indicates that an entity possesses or is associated with clothing that is customary or traditional within a particular culture or community.
- 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_69c008d9f4348190ab598a2913259a1c |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0683d7af881908d66d5230e1bfcb6 |
completed | March 22, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69c060eff524819094cee1c70a0c1ff4 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:33 p.m.