Triple
T29007225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French press |
E736468
|
entity |
| Predicate | producesCoffeeFlavor |
P72100
|
FINISHED |
| Object | rich |
—
|
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: rich | Statement: [French press, producesCoffeeFlavor, rich]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: producesCoffeeFlavor Context triple: [French press, producesCoffeeFlavor, rich]
-
A.
coffeeFlavorNotes
chosen
Indicates the characteristic taste and aroma qualities associated with a particular coffee, such as specific flavor notes perceived when it is consumed.
-
B.
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).
-
C.
coffeeProfile
Indicates the characteristic flavor, aroma, and strength attributes that define a particular coffee.
-
D.
coffeeDesignation
Indicates that one entity is designated or classified as a particular type, role, or category of coffee in relation to another entity.
-
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_69f077eb81e88190ad9ff62cbb9f555e |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69fcab6e888881908ca9e18660928a40 |
completed | May 7, 2026, 3:10 p.m. |
| PD | Predicate disambiguation | batch_69fc4562a5b88190bad48f083a6dcdfa |
completed | May 7, 2026, 7:55 a.m. |
Created at: April 28, 2026, 9:39 a.m.