Triple
T14266907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William II of Württemberg |
E353669
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object |
Bebenhausen
Bebenhausen is a historic village in Baden-Württemberg, Germany, best known for its well-preserved former Cistercian monastery and royal hunting lodge.
|
E1152688
|
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: Bebenhausen | Statement: [William II of Württemberg, placeOfDeath, Bebenhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bebenhausen Context triple: [William II of Württemberg, placeOfDeath, Bebenhausen]
-
A.
Babenhausen
Babenhausen is a small town in the German state of Hesse, known for its historic old town and location southeast of Frankfurt am Main.
-
B.
Babenhausen
Babenhausen is a market town in the Unterallgäu district of Bavaria, Germany, known for its historic center and role as a local administrative and service hub.
-
C.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
D.
Aidhausen
Aidhausen is a small municipality in the Lower Franconia region of Bavaria, Germany.
-
E.
Nennhausen
Nennhausen is a rural municipality in the Havelland district of Brandenburg, Germany, known for its historic manor house and surrounding natural landscapes.
- 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: Bebenhausen Triple: [William II of Württemberg, placeOfDeath, Bebenhausen]
Generated description
Bebenhausen is a historic village in Baden-Württemberg, Germany, best known for its well-preserved former Cistercian monastery and royal hunting lodge.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bebenhausen Target entity description: Bebenhausen is a historic village in Baden-Württemberg, Germany, best known for its well-preserved former Cistercian monastery and royal hunting lodge.
-
A.
Babenhausen
Babenhausen is a small town in the German state of Hesse, known for its historic old town and location southeast of Frankfurt am Main.
-
B.
Babenhausen
Babenhausen is a market town in the Unterallgäu district of Bavaria, Germany, known for its historic center and role as a local administrative and service hub.
-
C.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
D.
Aidhausen
Aidhausen is a small municipality in the Lower Franconia region of Bavaria, Germany.
-
E.
Nennhausen
Nennhausen is a rural municipality in the Havelland district of Brandenburg, Germany, known for its historic manor house and surrounding natural landscapes.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6358c2288190ac1fd26e688a605d |
completed | April 14, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff0b3017808190a44087056ba6a472 |
completed | May 9, 2026, 10:23 a.m. |
| NEDg | Description generation | batch_69ff0bb903f881909619cece7def68e4 |
completed | May 9, 2026, 10:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff0c81636c81909536e69b48c5c400 |
completed | May 9, 2026, 10:29 a.m. |
Created at: April 10, 2026, 1:09 a.m.