Triple
T27205377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coffee |
E683847
|
entity |
| Predicate | decaffeinationMethod |
P72099
|
FINISHED |
| Object | Solvent-based extraction |
—
|
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: Solvent-based extraction | Statement: [Coffee, decaffeinationMethod, Solvent-based extraction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: decaffeinationMethod Context triple: [Coffee, decaffeinationMethod, Solvent-based extraction]
-
A.
coffeeProcessingMethods
chosen
Indicates the methods or techniques used to transform raw coffee cherries or beans into a consumable coffee product.
-
B.
hasCaffeineContent
Indicates that one entity (typically a beverage or substance) possesses a specified amount or presence of caffeine.
-
C.
brewingMethod
Indicates the technique or process used to brew or prepare a beverage, typically coffee or tea.
-
D.
coffeeVariety
Indicates a relationship where a specific type or variety of coffee is associated with a coffee-related entity (such as a product, beverage, or plant).
-
E.
brewedAccordingTo
Indicates that something has been produced or prepared following a specified brewing method, recipe, or standard.
- 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_69eefad339a08190aeacb2a198f1a39b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f625e4327c8190aa93bdd93a046277 |
completed | May 2, 2026, 4:27 p.m. |
| PD | Predicate disambiguation | batch_69f620e38aec8190bb184edcdbd6da64 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 9:37 a.m.