Triple
T16816510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruwer River |
E408764
|
entity |
| Predicate | wineRegion |
P6176
|
FINISHED |
| Object | Ruwer |
E1071909
|
NE 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: Ruwer | Statement: [Ruwer River, wineRegion, Ruwer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruwer Context triple: [Ruwer River, wineRegion, Ruwer]
-
A.
Ruwer
chosen
Ruwer is a small wine-growing region in Germany’s Mosel area, noted for its cool climate and production of light, crisp white wines.
-
B.
Nahe
Nahe is a renowned German wine region, particularly celebrated for producing high-quality Riesling wines with diverse styles due to its varied soils and microclimates.
-
C.
Nahe
Nahe is a river in western Germany, known for flowing through the Nahe wine region before joining the Rhine.
-
D.
Lobau
Lobau is a large floodplain and protected natural reserve along the Danube in Vienna, known for its wetlands, biodiversity, and recreational value.
-
E.
Oderberg
Oderberg is a small historic town in northeastern Germany near the Oder River, known for its scenic natural surroundings and proximity to the Polish border.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b2e1de908190aa3508770fb865cf |
completed | April 18, 2026, 4:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00b297778c81909a2545c359739151 |
completed | May 10, 2026, 4:30 p.m. |
Created at: April 10, 2026, 5:23 a.m.