Triple
T7063921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veurne |
E164295
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Bad Bramstedt
Bad Bramstedt is a small spa town in northern Germany’s Schleswig-Holstein region, known for its therapeutic clinics and tranquil rural setting.
|
E638501
|
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: Bad Bramstedt | Statement: [Veurne, hasTwinTown, Bad Bramstedt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Bramstedt Context triple: [Veurne, hasTwinTown, Bad Bramstedt]
-
A.
Bad Brambach
Bad Brambach is a German spa town in the Vogtland region of Saxony, renowned for its mineral springs and therapeutic health resorts.
-
B.
Bad Doberan
Bad Doberan is a historic spa town in northern Germany known for its medieval Doberan Minster and proximity to the Baltic Sea coast.
-
C.
Bad Nauheim
Bad Nauheim is a spa town in the German state of Hesse, historically known for its therapeutic mineral springs and health resorts.
-
D.
Bad Bentheim
Bad Bentheim is a historic spa town in Lower Saxony, Germany, best known for its medieval Bentheim Castle and therapeutic mineral springs.
-
E.
Bad Iburg
Bad Iburg is a small spa town in Lower Saxony, Germany, known for its historic Iburg Castle and surrounding Teutoburg Forest scenery.
- 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: Bad Bramstedt Triple: [Veurne, hasTwinTown, Bad Bramstedt]
Generated description
Bad Bramstedt is a small spa town in northern Germany’s Schleswig-Holstein region, known for its therapeutic clinics and tranquil rural setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bad Bramstedt Target entity description: Bad Bramstedt is a small spa town in northern Germany’s Schleswig-Holstein region, known for its therapeutic clinics and tranquil rural setting.
-
A.
Bad Brambach
Bad Brambach is a German spa town in the Vogtland region of Saxony, renowned for its mineral springs and therapeutic health resorts.
-
B.
Bad Doberan
Bad Doberan is a historic spa town in northern Germany known for its medieval Doberan Minster and proximity to the Baltic Sea coast.
-
C.
Bad Nauheim
Bad Nauheim is a spa town in the German state of Hesse, historically known for its therapeutic mineral springs and health resorts.
-
D.
Bad Bentheim
Bad Bentheim is a historic spa town in Lower Saxony, Germany, best known for its medieval Bentheim Castle and therapeutic mineral springs.
-
E.
Bad Iburg
Bad Iburg is a small spa town in Lower Saxony, Germany, known for its historic Iburg Castle and surrounding Teutoburg Forest scenery.
- 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_69c688796c148190adb2f1596f595f22 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e45e80e08190bb1a79a6026d2cd5 |
completed | March 27, 2026, 8:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c788ba7af88190aeaf3205255af8ad |
completed | March 28, 2026, 7:52 a.m. |
| NEDg | Description generation | batch_69c7892a387c8190856eac695fbcfb02 |
completed | March 28, 2026, 7:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c789bc4fa081908cf40ec8ff189b90 |
completed | March 28, 2026, 7:56 a.m. |
Created at: March 27, 2026, 2:38 p.m.