Triple
T9623630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château de Fieuzal |
E232403
|
entity |
| Predicate | secondaryGrapeForWhite |
P39767
|
FINISHED |
| Object | Sémillon |
—
|
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: Sémillon | Statement: [Château de Fieuzal, secondaryGrapeForWhite, Sémillon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondaryGrapeForWhite Context triple: [Château de Fieuzal, secondaryGrapeForWhite, Sémillon]
-
A.
secondaryGrape
chosen
Indicates that one grape variety serves as a secondary or supporting component in a wine blend relative to the primary grape.
-
B.
secondaryWine
Indicates a relationship where one wine is designated as a secondary or supporting wine in relation to a primary wine.
-
C.
primaryGrapeVariety
Indicates that one entity is the main or predominant grape variety used in producing the other entity (typically a wine or wine-based product).
-
D.
synonymOfPrimaryGrape
Indicates that one grape variety is a synonym or alternate name for the primary grape variety specified.
-
E.
primaryGrapeUse
Indicates that a grape variety is primarily used for a particular purpose, such as winemaking, table consumption, or raisin production.
- 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_69ca848793ec8190a93a12383a754dc0 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9ad650a4819096258665bc3f410b |
completed | April 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69ccd5aa1d2c8190a287bf1cf4a3037e |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:10 p.m.