Triple
T14244656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rüdesheim am Rhein |
E353100
|
entity |
| Predicate | hasCityPart |
P12399
|
FINISHED |
| Object |
Presberg
Presberg is a small district of the town Rüdesheim am Rhein in the Rheingau region of Hesse, Germany, known for its scenic location above the Rhine and surrounding vineyards and forests.
|
E1087340
|
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: Presberg | Statement: [Rüdesheim am Rhein, hasCityPart, Presberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Presberg Context triple: [Rüdesheim am Rhein, hasCityPart, Presberg]
-
A.
Landensberg
Landensberg is a small municipality in the Bavarian region of southern Germany.
-
B.
Reinsberg
Reinsberg is a municipality in the German state of Saxony, located within the administrative district of Mittelsachsen.
-
C.
Bergharen
Bergharen is a village in the Dutch province of Gelderland, known for its historic church and rural surroundings.
-
D.
Gilserberg
Gilserberg is a small municipality in the German state of Hesse, known for its rural character and location within the Schwalm-Eder district.
-
E.
Seelenberg
Seelenberg is a small village that forms one of the local subdivisions of the municipality of Schmitten in Germany.
- 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: Presberg Triple: [Rüdesheim am Rhein, hasCityPart, Presberg]
Generated description
Presberg is a small district of the town Rüdesheim am Rhein in the Rheingau region of Hesse, Germany, known for its scenic location above the Rhine and surrounding vineyards and forests.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Presberg Target entity description: Presberg is a small district of the town Rüdesheim am Rhein in the Rheingau region of Hesse, Germany, known for its scenic location above the Rhine and surrounding vineyards and forests.
-
A.
Landensberg
Landensberg is a small municipality in the Bavarian region of southern Germany.
-
B.
Reinsberg
Reinsberg is a municipality in the German state of Saxony, located within the administrative district of Mittelsachsen.
-
C.
Bergharen
Bergharen is a village in the Dutch province of Gelderland, known for its historic church and rural surroundings.
-
D.
Gilserberg
Gilserberg is a small municipality in the German state of Hesse, known for its rural character and location within the Schwalm-Eder district.
-
E.
Seelenberg
Seelenberg is a small village that forms one of the local subdivisions of the municipality of Schmitten in Germany.
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6245d6a481909ef665748cd4d64c |
completed | April 14, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd282571ec819080d187ecec3ed925 |
completed | May 8, 2026, 12:02 a.m. |
| NEDg | Description generation | batch_69fd2a9da52481909f580eb0df3e1922 |
completed | May 8, 2026, 12:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd2b270c9c8190a573e53ca9af4e4b |
completed | May 8, 2026, 12:15 a.m. |
Created at: April 10, 2026, 1:08 a.m.