Triple
T28553226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turkish coffee |
E722941
|
entity |
| Predicate | filtering |
P164631
|
FINISHED |
| Object | unfiltered; grounds settle by gravity |
—
|
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: unfiltered; grounds settle by gravity | Statement: [Turkish coffee, filtering, unfiltered; grounds settle by gravity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filtering Context triple: [Turkish coffee, filtering, unfiltered; grounds settle by gravity]
-
A.
filter
Indicates that one entity selectively includes or excludes elements of another entity based on specified criteria or conditions.
-
B.
filterType
Indicates the specific category or method of filtering that is applied to a set of items or data.
-
C.
filterSystem
Indicates that one entity functions to remove or separate unwanted components, substances, or signals from another entity or system.
-
D.
usesFilter
Indicates that one entity applies or employs a filter (such as a criterion, condition, or processing mechanism) to another entity or set of data.
-
E.
nonChillFiltered
Indicates that a beverage, typically a spirit, has not undergone chill filtration to remove particles or compounds before bottling.
- 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_69f01a60204481909af1bb76247b8221 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f6504d2594819085cc5d1276b388ac |
completed | May 2, 2026, 7:28 p.m. |
| PD | Predicate disambiguation | batch_69f64cb0d8008190912e1430cfaf92aa |
completed | May 2, 2026, 7:12 p.m. |
| PDg | Predicate description generation | batch_69f64db8ee1881909362701d72ffe282 |
completed | May 2, 2026, 7:17 p.m. |
Created at: April 28, 2026, 3:44 a.m.