Triple
T14185285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | stroopwafels |
E351558
|
entity |
| Predicate | traditionalServingSuggestion |
P103073
|
FINISHED |
| Object | placed on top of a hot cup of coffee |
—
|
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: placed on top of a hot cup of coffee | Statement: [stroopwafels, traditionalServingSuggestion, placed on top of a hot cup of coffee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalServingSuggestion Context triple: [stroopwafels, traditionalServingSuggestion, placed on top of a hot cup of coffee]
-
A.
traditionallyServed
chosen
Indicates that one entity is customarily or conventionally presented, offered, or consumed together with another entity.
-
B.
servesTradition
Indicates that one entity upholds, maintains, or performs a tradition for the benefit or continuation of that tradition.
-
C.
servingSuggestionRed
Indicates that something is recommended or suggested to be served together with a red wine.
-
D.
servingStyle
Indicates how something (typically food or drink) is presented or offered for consumption or use.
-
E.
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).
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61cd5778819092a03597bcdcc182 |
completed | April 14, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69de05baed64819096590e5618a3a8ed |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:03 a.m.