Triple
T16309932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baroness Gösta von dem Bussche-Haddenhausen |
E396025
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
von dem Bussche-Haddenhausen
Von dem Bussche-Haddenhausen is a German noble family historically associated with the aristocracy of Lower Saxony.
|
E1205132
|
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: von dem Bussche-Haddenhausen | Statement: [Baroness Gösta von dem Bussche-Haddenhausen, familyName, von dem Bussche-Haddenhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: von dem Bussche-Haddenhausen Context triple: [Baroness Gösta von dem Bussche-Haddenhausen, familyName, von dem Bussche-Haddenhausen]
-
A.
Ochsenhausen
Ochsenhausen is a small historic town in the German state of Baden-Württemberg, best known for its former Benedictine monastery, Ochsenhausen Abbey.
-
B.
Nennhausen
Nennhausen is a rural municipality in the Havelland district of Brandenburg, Germany, known for its historic manor house and surrounding natural landscapes.
-
C.
Vippachedelhausen
Vippachedelhausen is a small municipality in the Weimarer Land district of Thuringia in central Germany.
-
D.
Völlinghausen
Völlinghausen is a village within the municipality of Möhnesee in North Rhine-Westphalia, Germany.
-
E.
Thannhausen
Thannhausen is a small town in the Bavarian region of Swabia in southern Germany.
- 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: von dem Bussche-Haddenhausen Triple: [Baroness Gösta von dem Bussche-Haddenhausen, familyName, von dem Bussche-Haddenhausen]
Generated description
Von dem Bussche-Haddenhausen is a German noble family historically associated with the aristocracy of Lower Saxony.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: von dem Bussche-Haddenhausen Target entity description: Von dem Bussche-Haddenhausen is a German noble family historically associated with the aristocracy of Lower Saxony.
-
A.
Ochsenhausen
Ochsenhausen is a small historic town in the German state of Baden-Württemberg, best known for its former Benedictine monastery, Ochsenhausen Abbey.
-
B.
Nennhausen
Nennhausen is a rural municipality in the Havelland district of Brandenburg, Germany, known for its historic manor house and surrounding natural landscapes.
-
C.
Vippachedelhausen
Vippachedelhausen is a small municipality in the Weimarer Land district of Thuringia in central Germany.
-
D.
Völlinghausen
Völlinghausen is a village within the municipality of Möhnesee in North Rhine-Westphalia, Germany.
-
E.
Thannhausen
Thannhausen is a small town in the Bavarian region of Swabia in southern Germany.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e288d9557c81909203cd47aebf0f44 |
completed | April 17, 2026, 7:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001fa517908190a29caa0156b1d1cd |
completed | May 10, 2026, 6:03 a.m. |
| NEDg | Description generation | batch_6a00204bc3dc8190af075707f8989e3a |
completed | May 10, 2026, 6:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00215cc7a48190a5c4219d15749aa2 |
completed | May 10, 2026, 6:10 a.m. |
Created at: April 10, 2026, 5:06 a.m.