Triple
T19508170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kreuzau |
E488079
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Üdingen
Üdingen is a village-level locality that forms part of the municipality of Kreuzau in the Düren district of North Rhine-Westphalia, Germany.
|
E1409267
|
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: Üdingen | Statement: [Kreuzau, hasSubdivision, Üdingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Üdingen Context triple: [Kreuzau, hasSubdivision, Üdingen]
-
A.
Böblingen
Böblingen is a town in the German state of Baden-Württemberg, near Stuttgart, known for its automotive and technology industries and its role as a regional economic center.
-
B.
Pulheim
Pulheim is a town in western Germany’s North Rhine-Westphalia, situated just northwest of Cologne within the broader Cologne/Bonn urban area.
-
C.
Walldorf
Walldorf is a town in southwestern Germany best known as the headquarters of software giant SAP and for its strong economic base in the technology sector.
-
D.
Waiblingen
Waiblingen is a town in the German state of Baden-Württemberg, located near Stuttgart and known as an important regional center in the Rems-Murr district.
-
E.
Poppenhausen
Poppenhausen is a small German town located in the Schweinfurt administrative region of northern Bavaria.
- 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: Üdingen Triple: [Kreuzau, hasSubdivision, Üdingen]
Generated description
Üdingen is a village-level locality that forms part of the municipality of Kreuzau in the Düren district of North Rhine-Westphalia, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Üdingen Target entity description: Üdingen is a village-level locality that forms part of the municipality of Kreuzau in the Düren district of North Rhine-Westphalia, Germany.
-
A.
Böblingen
Böblingen is a town in the German state of Baden-Württemberg, near Stuttgart, known for its automotive and technology industries and its role as a regional economic center.
-
B.
Pulheim
Pulheim is a town in western Germany’s North Rhine-Westphalia, situated just northwest of Cologne within the broader Cologne/Bonn urban area.
-
C.
Walldorf
Walldorf is a town in southwestern Germany best known as the headquarters of software giant SAP and for its strong economic base in the technology sector.
-
D.
Waiblingen
Waiblingen is a town in the German state of Baden-Württemberg, located near Stuttgart and known as an important regional center in the Rems-Murr district.
-
E.
Poppenhausen
Poppenhausen is a small German town located in the Schweinfurt administrative region of northern Bavaria.
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e635130e708190bb3d70e1abbade2a |
completed | April 20, 2026, 2:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0815e6d7b08190a81088e91751aab8 |
completed | May 16, 2026, 6:59 a.m. |
| NEDg | Description generation | batch_6a0817b8581c8190a3a2c9a9809f4baa |
completed | May 16, 2026, 7:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a081827a09c8190bf6f4e23926f6022 |
completed | May 16, 2026, 7:09 a.m. |
Created at: April 10, 2026, 1:40 p.m.