Triple
T32135857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tulumba |
E820761
|
entity |
| Predicate | typicallyConsumedAs |
P178113
|
FINISHED |
| Object | sweet snack |
—
|
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: sweet snack | Statement: [Tulumba, typicallyConsumedAs, sweet snack]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicallyConsumedAs Context triple: [Tulumba, typicallyConsumedAs, sweet snack]
-
A.
isTypicallyConsumedAs
chosen
Indicates that one entity is normally or customarily eaten or drunk in the form of another entity.
-
B.
isTypicallyConsumedFrom
Indicates that one entity is most commonly eaten or drunk using, contained in, or taken from the other entity.
-
C.
typicallyServedAs
Indicates that something is most commonly presented, used, or offered in a particular role, form, or function.
-
D.
intendedConsumption
Indicates that one entity is meant or designed to be consumed or used up by another entity.
-
E.
isTypicallyConsumedAfter
Indicates that one item is most commonly eaten, drunk, or otherwise consumed after another item in time or sequence.
- 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_69f349039e0c819091c7a7d322e3f46d |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379eaa540819095a1c5d9f3513f9b |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 12:30 a.m.