Triple
T5509451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heineken lager beer |
E144525
|
entity |
| Predicate | carbonationLevel |
P26165
|
FINISHED |
| Object | medium |
—
|
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: medium | Statement: [Heineken lager beer, carbonationLevel, medium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: carbonationLevel Context triple: [Heineken lager beer, carbonationLevel, medium]
-
A.
carbonation
chosen
Indicates that a substance, typically a beverage, has been infused with carbon dioxide gas, resulting in bubbles or fizziness.
-
B.
hasBitternessLevel
Indicates that an entity is associated with a specific degree or intensity of bitterness.
-
C.
acidityLevel
Indicates the degree or intensity of acidity associated with an entity, typically measured by pH or a comparable scale.
-
D.
typicalSweetnessLevel
Indicates the usual or characteristic degree of sweetness associated with something.
-
E.
isSoftDrinkVariantOf
Indicates that one soft drink is a specific version, flavor, or formulation derived from or based on another soft drink.
- 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_69c008f6b5048190a09064116062cf69 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f4ba90c8190ad22e5de84c545f9 |
completed | March 22, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69c01b07bde08190b3933b96bdc70dd5 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:33 p.m.