Triple
T12284356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aviation |
E292789
|
entity |
| Predicate | glasswareType |
P40472
|
FINISHED |
| Object | martini 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: martini glass | Statement: [Aviation, glasswareType, martini glass]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: glasswareType Context triple: [Aviation, glasswareType, martini glass]
-
A.
servingVessel
Indicates that one entity functions as the container or vessel used to serve another entity (such as food or drink).
-
B.
typeOfCup
chosen
Indicates the specific kind or category of cup that an entity is associated with or classified as.
-
C.
sparklingType
Indicates that one entity is classified as a specific type or category within the broader class of sparkling items or phenomena.
-
D.
wineCategory
Indicates the classification or type of wine that an entity (such as a specific wine) belongs to.
-
E.
dishType
Indicates the classification of a dish according to its culinary category or role (e.g., appetizer, main course, dessert).
- 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.