Triple
T9350282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District of Bad Tölz-Wolfratshausen |
E224997
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object |
Dietramszell
Dietramszell is a rural Bavarian municipality in southern Germany, known for its scenic countryside and historic monastery complex.
|
E848374
|
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: Dietramszell | Statement: [District of Bad Tölz-Wolfratshausen, containsMunicipality, Dietramszell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dietramszell Context triple: [District of Bad Tölz-Wolfratshausen, containsMunicipality, Dietramszell]
-
A.
Marlenheim
Marlenheim is a commune in northeastern France’s Alsace region, known as a historic wine-producing village and gateway to the area’s renowned vineyards and scenic countryside.
-
B.
Eberhardzell
Eberhardzell is a rural municipality in the district of Biberach in the German state of Baden-Württemberg.
-
C.
Deisenhausen
Deisenhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
D.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
E.
Fürstenzell
Fürstenzell is a market town and municipality in Lower Bavaria, Germany, known for its historic monastery and rural setting near the city of Passau.
- 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: Dietramszell Triple: [District of Bad Tölz-Wolfratshausen, containsMunicipality, Dietramszell]
Generated description
Dietramszell is a rural Bavarian municipality in southern Germany, known for its scenic countryside and historic monastery complex.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dietramszell Target entity description: Dietramszell is a rural Bavarian municipality in southern Germany, known for its scenic countryside and historic monastery complex.
-
A.
Marlenheim
Marlenheim is a commune in northeastern France’s Alsace region, known as a historic wine-producing village and gateway to the area’s renowned vineyards and scenic countryside.
-
B.
Eberhardzell
Eberhardzell is a rural municipality in the district of Biberach in the German state of Baden-Württemberg.
-
C.
Deisenhausen
Deisenhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
D.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
E.
Fürstenzell
Fürstenzell is a market town and municipality in Lower Bavaria, Germany, known for its historic monastery and rural setting near the city of Passau.
- 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_69ca842abfd48190949d71c3b86eeba8 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f9248c08190a7bb40feec2eb217 |
completed | April 1, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3549788608190a1949eb254e43a8e |
completed | April 6, 2026, 6:37 a.m. |
| NEDg | Description generation | batch_69d356211fd8819089db018473b959e9 |
completed | April 6, 2026, 6:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d356a1c48c81909820ad66d96c9cc5 |
completed | April 6, 2026, 6:45 a.m. |
Created at: March 30, 2026, 7:41 p.m.