Triple
T25585685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dürrenzimmern |
E641373
|
entity |
| Predicate | locatedInWineDistrict |
P93466
|
FINISHED |
| Object | Heilbronn wine-growing district |
—
|
NE NERFINISHED |
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: Heilbronn wine-growing district | Statement: [Dürrenzimmern, locatedInWineDistrict, Heilbronn wine-growing district]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInWineDistrict Context triple: [Dürrenzimmern, locatedInWineDistrict, Heilbronn wine-growing district]
-
A.
locatedInWineTourismCorridor
Indicates that something is situated within a designated wine tourism corridor or route.
-
B.
alsoProducesWineIn
Indicates that the subject, in addition to other products or activities, produces wine in the specified location or context.
-
C.
wineSubregion
chosen
Indicates that one region is a subregion within a larger, defined wine-producing region.
-
D.
wineLawRegionName
Indicates that a specific name refers to the legal wine-producing region defined by wine regulations.
-
E.
wineLawRegionFocus
Indicates that a legal rule or regulation specifically concerns or targets a particular geographic region in the context of wine.
- 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_69e75dc42b588190a98b58e0df359674 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f760a35b988190904e6267553ad2fe |
completed | May 3, 2026, 2:50 p.m. |
| PD | Predicate disambiguation | batch_69f75eb3d6f081908c933474eb359e3d |
completed | May 3, 2026, 2:41 p.m. |
Created at: April 21, 2026, 4:16 p.m.