Triple
T28607549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hui cuisine |
E724093
|
entity |
| Predicate | religiousDietaryLaw |
P6166
|
FINISHED |
| Object | Islamic dietary law |
—
|
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: Islamic dietary law | Statement: [Hui cuisine, religiousDietaryLaw, Islamic dietary law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: religiousDietaryLaw Context triple: [Hui cuisine, religiousDietaryLaw, Islamic dietary law]
-
A.
religiousLawAspect
Indicates that one entity represents a specific aspect, dimension, or component of a religious law associated with another entity.
-
B.
religiousLawView
Indicates a person's stance, interpretation, or opinion regarding a particular religious law or set of religious legal principles.
-
C.
kashrutPractice
Indicates the extent to which an entity follows or observes Jewish dietary laws (kashrut) in its practices or behavior.
-
D.
religiousRestriction
chosen
Indicates that one entity imposes, experiences, or is subject to limitations or rules based on religious beliefs or practices in relation to another entity or context.
-
E.
halachicCategory
Indicates the classification of something according to Jewish legal (halachic) categories or rulings.
- 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_69f01d816d7c8190a1fe27e3434041dc |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69fd485f57dc8190820365396d041991 |
completed | May 8, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69fd47d35da081908bec8901018d186c |
completed | May 8, 2026, 2:17 a.m. |
Created at: April 28, 2026, 4:28 a.m.