Triple
T17710967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turkish tea |
E441563
|
entity |
| Predicate | isTraditionallyBrewedIn |
P53110
|
FINISHED |
| Object | double teapot |
—
|
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 teapot | Statement: [Turkish tea, isTraditionallyBrewedIn, double teapot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTraditionallyBrewedIn Context triple: [Turkish tea, isTraditionallyBrewedIn, double teapot]
-
A.
brewedAccordingTo
Indicates that something has been produced or prepared following a specified brewing method, recipe, or standard.
-
B.
brewingMethod
chosen
Indicates the technique or process used to brew or prepare a beverage, typically coffee or tea.
-
C.
beerStyleOrigin
Indicates the place or region where a particular beer style was originally developed or first became established.
-
D.
traditionallyUsedBy
Indicates that something has been customarily or historically used by a particular person, group, or culture over time.
-
E.
coffeeDesignation
Indicates that one entity is designated or classified as a particular type, role, or category of coffee in relation to another entity.
- 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_69d8b9ea20b48190ace88bb46b01e6a9 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4729b5d3c819085613ed25dc6761d |
completed | April 19, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69e3cde601d4819097903f471f1fe99a |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:05 a.m.