Triple
T4538757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Remagen |
E107474
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Bandorf
Bandorf is a small district of the town of Remagen in the Rhineland-Palatinate region of western Germany.
|
E450990
|
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: Bandorf | Statement: [Remagen, hasSubdivision, Bandorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bandorf Context triple: [Remagen, hasSubdivision, Bandorf]
-
A.
Güstrow
Güstrow is a historic town in northern Germany known for its Renaissance castle, brick Gothic cathedral, and association with sculptor Ernst Barlach.
-
B.
Warnemünde
Warnemünde is a seaside district and popular Baltic Sea resort of the German city of Rostock, known for its wide sandy beaches and maritime atmosphere.
-
C.
Rostock
Rostock is a historic Hanseatic city in northern Germany known for its significant seaport on the Baltic Sea and its long maritime and trading tradition.
-
D.
Stralsund
Stralsund is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval old town and brick Gothic architecture.
-
E.
Angermünde
Angermünde is a historic small town in northeastern Germany’s Brandenburg state, known for its medieval architecture and location within the rural Uckermark region.
- 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: Bandorf Triple: [Remagen, hasSubdivision, Bandorf]
Generated description
Bandorf is a small district of the town of Remagen in the Rhineland-Palatinate region of western Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bandorf Target entity description: Bandorf is a small district of the town of Remagen in the Rhineland-Palatinate region of western Germany.
-
A.
Güstrow
Güstrow is a historic town in northern Germany known for its Renaissance castle, brick Gothic cathedral, and association with sculptor Ernst Barlach.
-
B.
Warnemünde
Warnemünde is a seaside district and popular Baltic Sea resort of the German city of Rostock, known for its wide sandy beaches and maritime atmosphere.
-
C.
Rostock
Rostock is a historic Hanseatic city in northern Germany known for its significant seaport on the Baltic Sea and its long maritime and trading tradition.
-
D.
Stralsund
Stralsund is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval old town and brick Gothic architecture.
-
E.
Angermünde
Angermünde is a historic small town in northeastern Germany’s Brandenburg state, known for its medieval architecture and location within the rural Uckermark region.
- 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_69bd43f922788190b7edfa294e39b178 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57ba327c8190a7f12e14077b1fa7 |
completed | March 20, 2026, 2:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdacfff41481908a5c97ab4fcb9259 |
completed | March 20, 2026, 8:24 p.m. |
| NEDg | Description generation | batch_69bdb32911cc8190a8624d54dad6355e |
completed | March 20, 2026, 8:50 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bdb3a0bf908190b9a029f47e6be941 |
completed | March 20, 2026, 8:52 p.m. |
Created at: March 20, 2026, 1:04 p.m.