Triple
T16559304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tinta Barroca |
E402293
|
entity |
| Predicate | typicalUseRatio |
P124051
|
FINISHED |
| Object | supporting variety in 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: supporting variety in blends | Statement: [Tinta Barroca, typicalUseRatio, supporting variety in blends]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalUseRatio Context triple: [Tinta Barroca, typicalUseRatio, supporting variety in blends]
-
A.
typicalUseDays
Indicates the usual or expected number of days over which something is used or intended to be used.
-
B.
typicalMeasure
Indicates the standard or characteristic quantitative measure typically associated with something, such as its usual size, weight, duration, or other magnitude.
-
C.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
D.
usageAmong
Indicates how frequently or in what manner something is used within a particular group, context, or population.
-
E.
typicalUnionDensity
Indicates the usual or characteristic level of labor union membership or representation within a given group, sector, or region.
- 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3576cceb881908579b56d91b15dec |
completed | April 18, 2026, 10:05 a.m. |
| PD | Predicate disambiguation | batch_69e296a47b7481909d9958158510c806 |
completed | April 17, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69e2d7f97e548190a474691a152bd8e8 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:15 a.m.