Triple
T6550833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malay weddings |
E151123
|
entity |
| Predicate | religiousCoreRite |
P2154
|
FINISHED |
| Object | akad nikah |
—
|
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: akad nikah | Statement: [Malay weddings, religiousCoreRite, akad nikah]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousCoreRite Context triple: [Malay weddings, religiousCoreRite, akad nikah]
-
A.
religiousElement
chosen
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
-
B.
religiousTraditions
Indicates a relationship where certain religious customs, practices, or belief systems are associated with or observed by an entity.
-
C.
religiousFunction
Indicates that one entity serves a religious role, purpose, or function in relation to another entity.
-
D.
religiousTextTradition
Indicates that a religious text is associated with, originates from, or is authoritative within a particular religious tradition or denomination.
-
E.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
- 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.