Triple
T4646650
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pithla Bhakri |
E102187
|
entity |
| Predicate | mainIngredientOfComponent |
P5291
|
FINISHED |
| Object | Pithla: gram flour (besan) |
—
|
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: Pithla: gram flour (besan) | Statement: [Pithla Bhakri, mainIngredientOfComponent, Pithla: gram flour (besan)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainIngredientOfComponent Context triple: [Pithla Bhakri, mainIngredientOfComponent, Pithla: gram flour (besan)]
-
A.
hasMainIngredient
chosen
Indicates that one entity is the primary or most significant ingredient used to make another entity.
-
B.
ingredientType
Indicates that one entity is classified as a specific type or category of ingredient in relation to another.
-
C.
usesIngredient
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
-
D.
isTypicallyGarnishedWith
Indicates that one item is commonly used as a garnish or decorative finishing element for another.
-
E.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
- 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_69bd43d71a308190afea7280841b0de8 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd6632708c8190b627d99363ab062c |
completed | March 20, 2026, 3:22 p.m. |
| PD | Predicate disambiguation | batch_69bd620fc5e081908325ac8e6a6384ab |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:14 p.m.