Triple
T11279767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhein-Sieg-Kreis |
E267032
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object |
Ahrweiler
Ahrweiler is a district in the German state of Rhineland-Palatinate, known for its wine-growing Ahr Valley and historic towns.
|
E939805
|
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: Ahrweiler | Statement: [Rhein-Sieg-Kreis, borders, Ahrweiler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ahrweiler Context triple: [Rhein-Sieg-Kreis, borders, Ahrweiler]
-
A.
Eschweiler
Eschweiler is a town in western Germany near Aachen, known for its industrial history and location in the state of North Rhine-Westphalia.
-
B.
Andernach
Andernach is a historic German town on the Rhine River in Rhineland-Palatinate, known for its medieval architecture and one of the world’s highest cold-water geysers.
-
C.
Neuß
Neuß is an alternative spelling of Neuss, a historic city on the Rhine in North Rhine-Westphalia, Germany.
-
D.
Monschau
Monschau is a historic small town in western Germany’s Eifel region, known for its well-preserved half-timbered houses, medieval center, and scenic setting along the Rur River.
-
E.
Neunkirchen
Neunkirchen is a town in southwestern Germany known as one of the major urban centers and former industrial hubs of the state of Saarland.
- 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: Ahrweiler Triple: [Rhein-Sieg-Kreis, borders, Ahrweiler]
Generated description
Ahrweiler is a district in the German state of Rhineland-Palatinate, known for its wine-growing Ahr Valley and historic towns.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ahrweiler Target entity description: Ahrweiler is a district in the German state of Rhineland-Palatinate, known for its wine-growing Ahr Valley and historic towns.
-
A.
Eschweiler
Eschweiler is a town in western Germany near Aachen, known for its industrial history and location in the state of North Rhine-Westphalia.
-
B.
Andernach
Andernach is a historic German town on the Rhine River in Rhineland-Palatinate, known for its medieval architecture and one of the world’s highest cold-water geysers.
-
C.
Neuß
Neuß is an alternative spelling of Neuss, a historic city on the Rhine in North Rhine-Westphalia, Germany.
-
D.
Monschau
Monschau is a historic small town in western Germany’s Eifel region, known for its well-preserved half-timbered houses, medieval center, and scenic setting along the Rur River.
-
E.
Neunkirchen
Neunkirchen is an industrial town in Austria’s Lower Austria region, known historically for its manufacturing and metalworking industries.
- 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e969b3448190940e2bd499d2d7de |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef127eaf588190aaca151ee4022f3c |
completed | April 27, 2026, 7:38 a.m. |
| NEDg | Description generation | batch_69ef354b3b3c8190b1c91dbf9c705a7d |
completed | April 27, 2026, 10:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ef5170ce9881908f2ecf3d5ada809a |
completed | April 27, 2026, 12:07 p.m. |
Created at: April 8, 2026, 9:31 p.m.