Triple
T9553632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regensburg (district) |
E230485
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Beratzhausen
Beratzhausen is a market town in the Upper Palatinate region of Bavaria, Germany, known for its historic center and location in the scenic Laber valley.
|
E899488
|
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: Beratzhausen | Statement: [Regensburg (district), contains, Beratzhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beratzhausen Context triple: [Regensburg (district), contains, Beratzhausen]
-
A.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
B.
Tussenhausen
Tussenhausen is a municipality in the district of Unterallgäu in Bavaria, Germany, known for its rural character and small villages such as Mattsies.
-
C.
Hettenshausen
Hettenshausen is a municipality in the district of Pfaffenhofen an der Ilm in Bavaria, Germany.
-
D.
Hubersdorf
Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
-
E.
Bleidenstadt
Bleidenstadt is a district of the town of Taunusstein in the Rheingau-Taunus region of Hesse, Germany, known for its historic church and small-town character.
- 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: Beratzhausen Triple: [Regensburg (district), contains, Beratzhausen]
Generated description
Beratzhausen is a market town in the Upper Palatinate region of Bavaria, Germany, known for its historic center and location in the scenic Laber valley.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Beratzhausen Target entity description: Beratzhausen is a market town in the Upper Palatinate region of Bavaria, Germany, known for its historic center and location in the scenic Laber valley.
-
A.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
B.
Tussenhausen
Tussenhausen is a municipality in the district of Unterallgäu in Bavaria, Germany, known for its rural character and small villages such as Mattsies.
-
C.
Hettenshausen
Hettenshausen is a municipality in the district of Pfaffenhofen an der Ilm in Bavaria, Germany.
-
D.
Hubersdorf
Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
-
E.
Bleidenstadt
Bleidenstadt is a district of the town of Taunusstein in the Rheingau-Taunus region of Hesse, Germany, known for its historic church and small-town character.
- 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_69ca847d3be8819099c9dad2a7e786f1 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99217de48190b528e14fd02ee987 |
completed | April 1, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3734e5e688190bbfa472547ef65e8 |
completed | April 18, 2026, 12:04 p.m. |
| NEDg | Description generation | batch_69e378dcc92c8190952d4acfee2a309c |
completed | April 18, 2026, 12:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e37be75a588190abb9569ef1e87279 |
completed | April 18, 2026, 12:41 p.m. |
Created at: March 30, 2026, 8:02 p.m.