Triple
T14724548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peine |
E345903
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Vöhrum
Vöhrum is a village and district of the town of Peine in Lower Saxony, Germany.
|
E1144466
|
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: Vöhrum | Statement: [Peine, hasSubdivision, Vöhrum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vöhrum Context triple: [Peine, hasSubdivision, Vöhrum]
-
A.
Vellinghausen
Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
-
B.
Völlinghausen
Völlinghausen is a village within the municipality of Möhnesee in North Rhine-Westphalia, Germany.
-
C.
Vellmar
Vellmar is a town in the German state of Hesse, located just north of Kassel.
-
D.
Werdohl
Werdohl is a town in the Märkischer Kreis district of North Rhine-Westphalia, Germany, known for its metalworking industry and location in the hilly Sauerland region.
-
E.
Göhrde
Göhrde is a municipality in Lower Saxony, Germany, known for its extensive forested areas and historical royal hunting grounds.
- 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: Vöhrum Triple: [Peine, hasSubdivision, Vöhrum]
Generated description
Vöhrum is a village and district of the town of Peine in Lower Saxony, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vöhrum Target entity description: Vöhrum is a village and district of the town of Peine in Lower Saxony, Germany.
-
A.
Vellinghausen
Vellinghausen is a village in western Germany known historically as the site of the Battle of Vellinghausen during the Seven Years' War.
-
B.
Völlinghausen
Völlinghausen is a village within the municipality of Möhnesee in North Rhine-Westphalia, Germany.
-
C.
Vellmar
Vellmar is a town in the German state of Hesse, located just north of Kassel.
-
D.
Werdohl
Werdohl is a town in the Märkischer Kreis district of North Rhine-Westphalia, Germany, known for its metalworking industry and location in the hilly Sauerland region.
-
E.
Göhrde
Göhrde is a municipality in Lower Saxony, Germany, known for its extensive forested areas and historical royal hunting grounds.
- 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_69d822e5911c8190ba589f957dbd9ba7 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec25e9a14819081fa06fc601f295d |
completed | April 14, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd1de868819084d71f75210d14f5 |
completed | May 9, 2026, 7:07 a.m. |
| NEDg | Description generation | batch_69fedec141f081908143c72eac1694db |
completed | May 9, 2026, 7:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fedf13876c8190b7b08cd8e00a05ea |
completed | May 9, 2026, 7:15 a.m. |
Created at: April 10, 2026, 1:29 a.m.