Triple
T12285216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vesper |
E292811
|
entity |
| Predicate | hasServingGlass |
P72115
|
FINISHED |
| Object | cocktail glass |
—
|
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: cocktail glass | Statement: [Vesper, hasServingGlass, cocktail glass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasServingGlass Context triple: [Vesper, hasServingGlass, cocktail glass]
-
A.
servingVessel
chosen
Indicates that one entity functions as the container or vessel used to serve another entity (such as food or drink).
-
B.
hasSparklingWine
Indicates that an entity possesses, includes, or is associated with sparkling wine.
-
C.
typeOfCup
Indicates the specific kind or category of cup that an entity is associated with or classified as.
-
D.
hasServingCustom
Indicates that an entity follows or applies a particular custom, style, or convention in how something (such as food, drink, or service) is served.
-
E.
cupWonWith
Indicates that a particular cup or tournament victory was achieved using or in association with a specified entity (such as a team, player, or equipment).
- 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.