Triple
T11213323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sta. Rita Hills AVA |
E265363
|
entity |
| Predicate | bestSuitedFor |
P18991
|
FINISHED |
| Object | Burgundian grape varieties |
—
|
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: Burgundian grape varieties | Statement: [Sta. Rita Hills AVA, bestSuitedFor, Burgundian grape varieties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestSuitedFor Context triple: [Sta. Rita Hills AVA, bestSuitedFor, Burgundian grape varieties]
-
A.
isSuitableFor
chosen
Indicates that one entity is appropriate, fitting, or well-matched for use, application, or association with another entity.
-
B.
lessSuitableFor
Indicates that one entity is comparatively less appropriate, effective, or fitting than another for a given purpose, context, or condition.
-
C.
appliesPrimarilyTo
Indicates that a property, rule, or characteristic is mainly relevant or intended for a particular entity or group, more than for others.
-
D.
primarilyFor
Indicates that something is mainly intended, designed, or used for a particular purpose, function, or beneficiary, even if it may have secondary uses.
-
E.
featuresSuit
Indicates that one entity includes or presents a particular suit (e.g., clothing, armor, or outfit) as a notable component or attribute.
- 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_69d6aac59460819089b9848b27f57848 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8d7f47c8190b78c640ff1a01943 |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cfbbb188190861efd5d94fe27da |
completed | April 9, 2026, 8:02 a.m. |
Created at: April 8, 2026, 9:30 p.m.