Triple
T9623626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château de Fieuzal |
E232403
|
entity |
| Predicate | wineClassificationRegion |
P89316
|
FINISHED |
| Object | Graves classification of 1953 and 1959 |
—
|
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: Graves classification of 1953 and 1959 | Statement: [Château de Fieuzal, wineClassificationRegion, Graves classification of 1953 and 1959]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineClassificationRegion Context triple: [Château de Fieuzal, wineClassificationRegion, Graves classification of 1953 and 1959]
-
A.
wineRegion
Indicates the geographical region or area where a particular wine is produced or originates.
-
B.
wineLawRegionName
Indicates that a specific name refers to the legal wine-producing region defined by wine regulations.
-
C.
notableWineRegionCountry
Indicates that a country is recognized as a notable or significant wine-producing region.
-
D.
wineAppellation
Indicates that a wine originates from, and is classified under, a specific geographic appellation or designated wine-producing region.
-
E.
wineRegionPartOf
Indicates that a wine-producing region is geographically or administratively contained within a larger wine region or area.
- 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_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. |
| PDg | Predicate description generation | batch_69ccd93fc45c8190a823305e461e581d |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:10 p.m.