Triple
T28553228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turkish coffee |
E722941
|
entity |
| Predicate | preparationTool |
P28572
|
FINISHED |
| Object | cezve |
—
|
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: cezve | Statement: [Turkish coffee, preparationTool, cezve]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: preparationTool Context triple: [Turkish coffee, preparationTool, cezve]
-
A.
preparationBy
Indicates that one entity is created, assembled, or made ready through the actions or processes performed by another entity.
-
B.
toolIn
chosen
Indicates that one entity is a tool or instrument used in or associated with another entity or context.
-
C.
preparationRequirement
Indicates that one entity must be prepared, configured, or made ready as a necessary condition before another entity, action, or process can occur or be valid.
-
D.
studiesFor
Indicates that one entity engages in studying or academic preparation with the purpose of achieving or supporting another entity (such as a goal, exam, or qualification).
-
E.
studentPreparation
Indicates the extent and manner in which a student is made ready or equipped for a particular task, course, or learning activity.
- 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_69f01a60204481909af1bb76247b8221 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f65a6c900881908f18b61273d7bf8d |
completed | May 2, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69f659ce58408190ba9e007b4810d4d0 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 3:44 a.m.