Triple
T22517441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ABC Extra Stout |
E556683
|
entity |
| Predicate | hasRoastLevel |
P117501
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [ABC Extra Stout, hasRoastLevel, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRoastLevel Context triple: [ABC Extra Stout, hasRoastLevel, high]
-
A.
roastProfile
chosen
Indicates the specific roasting characteristics or level applied to an item (typically coffee), defining how it was roasted.
-
B.
typicalRoastUse
Indicates that something is commonly or characteristically used for roasting.
-
C.
hasBitternessLevel
Indicates that an entity is associated with a specific degree or intensity of bitterness.
-
D.
hasPeatingLevelRange
Indicates that something is associated with a specified range of peatiness levels, typically expressing how peated or smoky it is within defined minimum and maximum bounds.
-
E.
nutsLevel
Indicates the degree or intensity to which something or someone is considered crazy, eccentric, or wildly unconventional.
- 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_69e11e5657e881909f16ca58352c50da |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15e2df59c81909c4ae2f20f1cbb32 |
completed | April 29, 2026, 1:26 a.m. |
| PD | Predicate disambiguation | batch_69ee625e3b408190a60c759fb0b28fe2 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 16, 2026, 8:50 p.m.