Triple
T10300593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château La Tour-Martillac |
E241616
|
entity |
| Predicate | primaryWhiteBlendStyle |
P2077
|
FINISHED |
| Object | Sauvignon Blanc–Sémillon blend |
—
|
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: Sauvignon Blanc–Sémillon blend | Statement: [Château La Tour-Martillac, primaryWhiteBlendStyle, Sauvignon Blanc–Sémillon blend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryWhiteBlendStyle Context triple: [Château La Tour-Martillac, primaryWhiteBlendStyle, Sauvignon Blanc–Sémillon blend]
-
A.
primaryWhiteVariety
Indicates that one entity is the primary white (light-skinned or white-colored) variety or form of another entity.
-
B.
typicalBlendStyle
chosen
Indicates the usual or characteristic way in which two or more elements are combined or mixed together.
-
C.
typicalWhiteStyleDescriptor
Indicates that something is described as having characteristics commonly associated with a stereotypical white cultural style or aesthetic.
-
D.
styleWhite
Indicates that one entity has a white style, appearance, or coloration in relation to another or within a given context.
-
E.
primaryStyle
Indicates the main or predominant style associated with an entity, distinguishing it from other secondary or supporting styles.
- 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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2eefe8881908a672c4dca7657ca |
completed | April 7, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f35e548190be3b4d92d65d2d20 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:44 a.m.