Triple
T11068419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Islam in Yemen |
E261682
|
entity |
| Predicate | influencesDiet |
P95772
|
FINISHED |
| Object | halal dietary practices 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: halal dietary practices in Yemen | Statement: [Islam in Yemen, influencesDiet, halal dietary practices in Yemen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencesDiet Context triple: [Islam in Yemen, influencesDiet, halal dietary practices in Yemen]
-
A.
diet
Indicates that an entity regularly consumes a particular type or range of food as its primary source of nutrition.
-
B.
dietAdvocated
chosen
Indicates that one entity promotes, recommends, or supports a particular diet for another entity or audience.
-
C.
nutritionType
Indicates the specific category or kind of nutritional characteristic or value associated with an entity.
-
D.
cuisineInfluence
Indicates that one cuisine has had a notable impact on the development, style, or characteristics of another cuisine.
-
E.
focusesOnNutrition
Indicates that the subject’s primary attention, activity, or content is centered on nutrition-related topics, practices, or goals.
- 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.