Triple
T6550874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malay weddings |
E151123
|
entity |
| Predicate | genderNorm |
P60410
|
FINISHED |
| Object | modest dress code |
—
|
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 dress code | Statement: [Malay weddings, genderNorm, modest dress code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderNorm Context triple: [Malay weddings, genderNorm, modest dress code]
-
A.
genderNorms
chosen
Indicates socially constructed expectations or rules about how individuals should behave, appear, or identify based on their perceived gender.
-
B.
genderConfiguration
Indicates how the genders of the involved entities are arranged or combined within a particular relationship or context.
-
C.
genderRule
Indicates a rule or constraint that determines how gender-related properties or classifications should be assigned or interpreted in a given context.
-
D.
genderUsage
Indicates how a particular gender is applied, referenced, or treated within a given context or system.
-
E.
genderVariant
Indicates that an entity’s gender identity or expression differs from traditional or expected norms associated with their assigned sex or gender.
- 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_69c687f3fd60819083bfa583e5bcfa71 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c1b15d3481908ae66e3d7564b352 |
completed | March 27, 2026, 5:43 p.m. |
| PD | Predicate disambiguation | batch_69c6acf6d4148190914b19e9affd8c76 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:51 p.m.