Triple
T2687537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Cloud |
E57518
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object |
Rüthen
Rüthen is a small historic town in North Rhine-Westphalia, Germany, known for its medieval architecture and location in the scenic Sauerland region.
|
E300331
|
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: Rüthen | Statement: [Saint-Cloud, twinTown, Rüthen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rüthen Context triple: [Saint-Cloud, twinTown, Rüthen]
-
A.
Nesslau-Krummenau
Nesslau-Krummenau was a former municipality in the canton of St. Gallen in northeastern Switzerland, known for its rural Alpine setting and merger into the larger municipality of Nesslau.
-
B.
Unterwallenstadt
Unterwallenstadt is a small locality that forms part of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
-
C.
Blaubeuren
Blaubeuren is a historic town in the Alb-Donau district of Baden-Württemberg, Germany, known for its medieval old town and the karst spring Blautopf.
-
D.
Riehen
Riehen is a municipality in the canton of Basel-Stadt in northern Switzerland, known as a residential suburb of Basel near the German border.
-
E.
Boblingen
Böblingen is a town in the German state of Baden-Württemberg, known for its automotive industry presence and proximity to Stuttgart.
- 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: Rüthen Triple: [Saint-Cloud, twinTown, Rüthen]
Generated description
Rüthen is a small historic town in North Rhine-Westphalia, Germany, known for its medieval architecture and location in the scenic Sauerland region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rüthen Target entity description: Rüthen is a small historic town in North Rhine-Westphalia, Germany, known for its medieval architecture and location in the scenic Sauerland region.
-
A.
Nesslau-Krummenau
Nesslau-Krummenau was a former municipality in the canton of St. Gallen in northeastern Switzerland, known for its rural Alpine setting and merger into the larger municipality of Nesslau.
-
B.
Unterwallenstadt
Unterwallenstadt is a small locality that forms part of the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
-
C.
Blaubeuren
Blaubeuren is a historic town in the Alb-Donau district of Baden-Württemberg, Germany, known for its medieval old town and the karst spring Blautopf.
-
D.
Riehen
Riehen is a municipality in the canton of Basel-Stadt in northern Switzerland, known as a residential suburb of Basel near the German border.
-
E.
Boblingen
Böblingen is a town in the German state of Baden-Württemberg, known for its automotive industry presence and proximity to Stuttgart.
- 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_69ab4a5028388190a36f3baf1588309e |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd9f080108190ab662a3a064cb5a9 |
completed | March 7, 2026, 7:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc63b76e0819084c4d2bd4a9e6d78 |
completed | March 10, 2026, 7:20 a.m. |
| NEDg | Description generation | batch_69afcaaca2148190b61498e5139d664d |
completed | March 10, 2026, 7:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afcb43e9b88190a99b1bb2e62430da |
completed | March 10, 2026, 7:41 a.m. |
Created at: March 6, 2026, 9:54 p.m.