Triple
T27635825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stella Artois |
E696465
|
entity |
| Predicate | hasSignatureGlassware |
P106954
|
FINISHED |
| Object | Stella Artois chalice |
—
|
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: Stella Artois chalice | Statement: [Stella Artois, hasSignatureGlassware, Stella Artois chalice]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSignatureGlassware Context triple: [Stella Artois, hasSignatureGlassware, Stella Artois chalice]
-
A.
glassType
Indicates the specific kind or category of glass associated with or used by an entity.
-
B.
signatureDrink
Indicates that a particular drink is the characteristic or specially associated beverage of an entity (such as a person, venue, or brand).
-
C.
hasGlassworks
Indicates that one entity possesses, operates, or is associated with a glassworks facility or glassmaking operation.
-
D.
hasCorkscrew
Indicates that one entity possesses or is equipped with a corkscrew.
-
E.
hasSignatureEquipment
chosen
Indicates that an entity is associated with a distinctive or characteristic piece of equipment that is uniquely or notably linked to it.
- 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_69ef5909f3848190805f35b76833e722 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f6c1265c208190aacd2b551f8f0f82 |
completed | May 3, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 27, 2026, 2:23 p.m.