Triple
T4646678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pithla Bhakri |
E102187
|
entity |
| Predicate | oftenConsumedAs |
P53136
|
FINISHED |
| Object | everyday meal |
—
|
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: everyday meal | Statement: [Pithla Bhakri, oftenConsumedAs, everyday meal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenConsumedAs Context triple: [Pithla Bhakri, oftenConsumedAs, everyday meal]
-
A.
typicallyEatenAt
chosen
Indicates that something is most commonly or customarily eaten during a particular time, event, or context.
-
B.
isEatenIn
Indicates that one entity (typically food) is consumed within the context, location, or occasion specified by another entity.
-
C.
isTypicallyGarnishedWith
Indicates that one item is commonly used as a garnish or decorative finishing element for another.
-
D.
servesMostly
Indicates that one entity primarily functions to serve, support, or cater to another entity, more than to any other.
-
E.
culinaryUse
Indicates that one entity is used in the preparation, flavoring, or serving of food or drink 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.