Triple
T12284572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Espresso Martini |
E292795
|
entity |
| Predicate | typicalStrainingMethod |
P104041
|
FINISHED |
| Object | double strained |
—
|
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: double strained | Statement: [Espresso Martini, typicalStrainingMethod, double strained]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalStrainingMethod Context triple: [Espresso Martini, typicalStrainingMethod, double strained]
-
A.
strainType
Indicates the specific variety or subtype classification within a broader category of strains (e.g., biological, chemical, or product strains).
-
B.
targetStrain
Indicates that one entity is the specific strain (e.g., genetic, microbial, or biological variant) that is the focus or objective of another entity’s action, study, or effect.
-
C.
digestiveMethod
Indicates the way or process by which an entity digests or breaks down food or nutrients.
-
D.
stainMethod
Indicates the technique or procedure used to apply a stain to a material or specimen.
-
E.
stomachType
Indicates the kind or classification of stomach an entity has, typically describing its structural or functional type.
- 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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9261e1570819084bb4fdb44aa6aea |
completed | April 10, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69d91c4d9a9c8190aeb7beaf9792d8f0 |
completed | April 10, 2026, 3:50 p.m. |
| PDg | Predicate description generation | batch_69d9261b7f088190b69fe6961015fce3 |
completed | April 10, 2026, 4:32 p.m. |
Created at: April 8, 2026, 9:52 p.m.