Triple
T32135454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mezze |
E820753
|
entity |
| Predicate | typicalDishIncludes |
P148210
|
FINISHED |
| Object | hummus |
—
|
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: hummus | Statement: [Mezze, typicalDishIncludes, hummus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDishIncludes Context triple: [Mezze, typicalDishIncludes, hummus]
-
A.
isTypicallyEatenWith
chosen
Indicates that one item is commonly consumed together with another as part of the same eating occasion or dish.
-
B.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
-
C.
isTypicallyGarnishedWith
Indicates that one item is commonly used as a garnish or decorative finishing element for another.
-
D.
isTypicallyServedFor
Indicates that one item is most commonly or customarily served as a meal or course for the other (e.g., a dish typically served for breakfast, lunch, or dinner).
-
E.
isTypicallyConsumedAs
Indicates that one entity is normally or customarily eaten or drunk in the form of 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_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.