Triple
T19916496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trop50 |
E478677
|
entity |
| Predicate | hasServingUse |
P137805
|
FINISHED |
| Object | breakfast beverage |
—
|
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: breakfast beverage | Statement: [Trop50, hasServingUse, breakfast beverage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasServingUse Context triple: [Trop50, hasServingUse, breakfast beverage]
-
A.
servesUse
Indicates that one entity is used by or functions to serve the purpose or needs of another entity.
-
B.
isServed
Indicates that one entity provides or delivers a service, product, or assistance to another entity.
-
C.
canServeIn
Indicates that one entity is eligible, authorized, or suitable to perform a role, function, or duty within another entity, context, or organization.
-
D.
intendedToServe
Indicates that one entity was designed, planned, or purposed specifically to benefit, assist, or fulfill the needs of another entity.
-
E.
isServedOn
Indicates that one item (typically food or drink) is presented or provided atop or together with a particular surface, container, or accompaniment.
- F. None of above. chosen
Provenance (4 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65994f4608190b79771ddea1040f5 |
completed | April 20, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69e537f070b481908958e0e5911dcdc1 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:53 p.m.