Triple
T10950913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamburg S-Bahn line S1 |
E258722
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object |
Wedel
Wedel is a town on the outskirts of Hamburg, Germany, known for being a suburban terminus of the city's S-Bahn network.
|
E894696
|
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: Wedel | Statement: [Hamburg S-Bahn line S1, terminus, Wedel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wedel Context triple: [Hamburg S-Bahn line S1, terminus, Wedel]
-
A.
Oudenburg
Oudenburg is a small historic town in the Belgian province of West Flanders, known for its Roman heritage and medieval abbey.
-
B.
Wolkenburg
Wolkenburg is a prominent hill in Germany’s Siebengebirge range, known for its volcanic origin and scenic views over the Rhine Valley.
-
C.
Stolberg
Stolberg is a historic German town in the Harz region, known for its well-preserved medieval architecture and role in early Reformation-era history.
-
D.
Badenburg
Badenburg is an ornate pavilion within Munich’s Nymphenburg Palace park, known for its richly decorated interiors and historical bathing hall.
-
E.
Wittlich
Wittlich is a small town in the Rhineland-Palatinate region of western Germany, known for its wine production and historic old town.
- 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: Wedel Triple: [Hamburg S-Bahn line S1, terminus, Wedel]
Generated description
Wedel is a town on the outskirts of Hamburg, Germany, known for being a suburban terminus of the city's S-Bahn network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wedel Target entity description: Wedel is a town on the outskirts of Hamburg, Germany, known for being a suburban terminus of the city's S-Bahn network.
-
A.
Oudenburg
Oudenburg is a small historic town in the Belgian province of West Flanders, known for its Roman heritage and medieval abbey.
-
B.
Wolkenburg
Wolkenburg is a prominent hill in Germany’s Siebengebirge range, known for its volcanic origin and scenic views over the Rhine Valley.
-
C.
Stolberg
Stolberg is a historic German town in the Harz region, known for its well-preserved medieval architecture and role in early Reformation-era history.
-
D.
Badenburg
Badenburg is an ornate pavilion within Munich’s Nymphenburg Palace park, known for its richly decorated interiors and historical bathing hall.
-
E.
Wittlich
Wittlich is a small town in the Rhineland-Palatinate region of western Germany, known for its wine production and historic old town.
- 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770fc156c8190826e124c13ce7242 |
completed | April 9, 2026, 9:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e23c57038c819087671177c2ed5633 |
completed | April 17, 2026, 1:57 p.m. |
| NEDg | Description generation | batch_69e24543bd2c8190a3c807baa76c30f6 |
completed | April 17, 2026, 2:35 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e25d11ef24819091e730ae2416a058 |
completed | April 17, 2026, 4:17 p.m. |
Created at: April 8, 2026, 9:23 p.m.