Triple
T10959817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arabica |
E258939
|
entity |
| Predicate | typicalRoastUse |
P96850
|
FINISHED |
| Object | filter coffee |
—
|
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: filter coffee | Statement: [Arabica, typicalRoastUse, filter coffee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRoastUse Context triple: [Arabica, typicalRoastUse, filter coffee]
-
A.
typicalPreparation
Indicates the usual or standard way in which something is prepared or made.
-
B.
usesIngredient
Indicates that one entity employs or incorporates another entity as an ingredient in its composition or creation.
-
C.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
D.
BakerYield
Indicates the amount or output produced by a baker, typically in terms of quantity or volume of baked goods resulting from a given process or batch.
-
E.
estimatedTeaWeight
Indicates the quantified amount of tea that is approximated or predicted in weight rather than precisely measured.
- F. None of above. chosen
Provenance (4 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d77127b10481908ad1efafb2a338d1 |
completed | April 9, 2026, 9:28 a.m. |
| PD | Predicate disambiguation | batch_69d72e874f48819096ffa878f90c7d5b |
completed | April 9, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69d7322370648190ba14cdd6fb4cdcb0 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:23 p.m.