Triple
T12965746
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orange (sports drink flavor) |
E321256
|
entity |
| Predicate | isCommonlyServed |
P104047
|
FINISHED |
| Object | chilled |
—
|
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: chilled | Statement: [Orange (sports drink flavor), isCommonlyServed, chilled]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isCommonlyServed Context triple: [Orange (sports drink flavor), isCommonlyServed, chilled]
-
A.
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).
-
B.
isTypicallyServedIn
Indicates that something (such as a food or drink) is most commonly or customarily presented or contained within a particular type of vessel or container.
-
C.
servesMostly
Indicates that one entity primarily functions to serve, support, or cater to another entity, more than to any other.
-
D.
typicallyServedAs
Indicates that something is most commonly presented, used, or offered in a particular role, form, or function.
-
E.
isTypicallyConsumedFrom
chosen
Indicates that one entity is most commonly eaten or drunk using, contained in, or taken from the other 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_69d80763bd6c819094437da5b20b01d2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:28 p.m.