Triple
T12284758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Long Island Iced Tea |
E292800
|
entity |
| Predicate | garnishedWith |
P56695
|
FINISHED |
| Object | lemon wedge |
—
|
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: lemon wedge | Statement: [Long Island Iced Tea, garnishedWith, lemon wedge]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: garnishedWith Context triple: [Long Island Iced Tea, garnishedWith, lemon wedge]
-
A.
isTypicallyGarnishedWith
chosen
Indicates that one item is commonly used as a garnish or decorative finishing element for another.
-
B.
adornedWith
Indicates that one entity is decorated, embellished, or ornamented by another entity.
-
C.
servesWith
Indicates that one entity is customarily presented, used, or consumed together with another as a complementary accompaniment.
-
D.
hasGravy
Indicates that one entity is accompanied by, covered with, or served with gravy in relation to another entity or context.
-
E.
servesDish
Indicates that one entity prepares and presents a specific dish as food for 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9261e1570819084bb4fdb44aa6aea |
completed | April 10, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69d91c4d9a9c8190aeb7beaf9792d8f0 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.