Triple
T16782300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carinyena |
E407884
|
entity |
| Predicate | typicalUseInRegion |
P15483
|
FINISHED |
| Object | component of Mediterranean red blends |
—
|
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: component of Mediterranean red blends | Statement: [Carinyena, typicalUseInRegion, component of Mediterranean red blends]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalUseInRegion Context triple: [Carinyena, typicalUseInRegion, component of Mediterranean red blends]
-
A.
hasTypicalUsageRegion
chosen
Indicates that something is most commonly or characteristically used within a particular geographic region.
-
B.
usedInCountryOrRegion
Indicates that something (such as an item, concept, or practice) is utilized or applied within a specified country or region.
-
C.
usedInRegion
Indicates that something is utilized or applied within a specific geographic or administrative region.
-
D.
usedInCountry
Indicates that something is utilized, applied, or in operation within the specified country.
-
E.
usedInCountries
Indicates that something is utilized or applied within one or more specified countries.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b217b2108190bbba262a3b324509 |
completed | April 18, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.