Triple
T13972558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elbling |
E336100
|
entity |
| Predicate | regionOfCultivation |
P2078
|
FINISHED |
| Object |
Ruwer
Ruwer is a small wine-growing region in Germany’s Mosel area, noted for its cool climate and production of light, crisp white wines.
|
E1071909
|
NE FINISHED |
How this triple was built (4 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: [Elbling, regionOfCultivation, Ruwer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ruwer Context triple: [Elbling, regionOfCultivation, Ruwer]
-
A.
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.
-
B.
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.
-
C.
Werre
The Werre is a river in North Rhine-Westphalia, Germany, that flows through towns such as Detmold and Herford before joining the Weser.
-
D.
Rissne
Rissne is a residential district and urban area in the Stockholm metropolitan region of Sweden, known for its mix of apartment housing and proximity to public transit.
-
E.
Rohe
Rohe is the surname of American actress and dancer Vera-Ellen, known for her roles in classic Hollywood musicals.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ruwer Triple: [Elbling, regionOfCultivation, Ruwer]
Generated description
Ruwer is a small wine-growing region in Germany’s Mosel area, noted for its cool climate and production of light, crisp white wines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ruwer Target entity description: Ruwer is a small wine-growing region in Germany’s Mosel area, noted for its cool climate and production of light, crisp white wines.
-
A.
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.
-
B.
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.
-
C.
Werre
The Werre is a river in North Rhine-Westphalia, Germany, that flows through towns such as Detmold and Herford before joining the Weser.
-
D.
Rissne
Rissne is a residential district and urban area in the Stockholm metropolitan region of Sweden, known for its mix of apartment housing and proximity to public transit.
-
E.
Rohe
Rohe is the surname of American actress and dancer Vera-Ellen, known for her roles in classic Hollywood musicals.
- F. None of above. chosen
Provenance (5 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e8eae40819080dd4bd25c73b6d6 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1df334c8190a3d65198cc3d11f6 |
completed | May 6, 2026, 8:17 p.m. |
| NEDg | Description generation | batch_69fba5918348819084fa4235eec6eee0 |
completed | May 6, 2026, 8:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fba6b5e4f4819088e8a0629e17e4cc |
completed | May 6, 2026, 8:38 p.m. |
Created at: April 9, 2026, 10:18 p.m.