Triple
T13227567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ladenburg |
E314920
|
entity |
| Predicate | hasLandmark |
P105
|
FINISHED |
| Object |
Bischofshof
Bischofshof is a historic former episcopal residence and notable architectural landmark located in the German town of Ladenburg.
|
E1028038
|
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: Bischofshof | Statement: [Ladenburg, hasLandmark, Bischofshof]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bischofshof Context triple: [Ladenburg, hasLandmark, Bischofshof]
-
A.
Wehofen
Wehofen is a district of the Walsum area in the city of Duisburg in North Rhine-Westphalia, Germany.
-
B.
Bischofsheim an der Rhön
Bischofsheim an der Rhön is a small town in northern Bavaria, Germany, known for its location in the scenic Rhön Mountains and its access to hiking and nature tourism.
-
C.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
D.
Bischofswiesen
Bischofswiesen is a municipality in the Bavarian Alps of southeastern Germany, known for its scenic mountain landscapes and proximity to Berchtesgaden.
-
E.
Reichertshofen
Reichertshofen is a market town and municipality in Upper Bavaria, Germany, known for its location near the confluence of the Paar and Ilm rivers and its proximity to the city of Ingolstadt.
- 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: Bischofshof Triple: [Ladenburg, hasLandmark, Bischofshof]
Generated description
Bischofshof is a historic former episcopal residence and notable architectural landmark located in the German town of Ladenburg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bischofshof Target entity description: Bischofshof is a historic former episcopal residence and notable architectural landmark located in the German town of Ladenburg.
-
A.
Wehofen
Wehofen is a district of the Walsum area in the city of Duisburg in North Rhine-Westphalia, Germany.
-
B.
Bischofsheim an der Rhön
Bischofsheim an der Rhön is a small town in northern Bavaria, Germany, known for its location in the scenic Rhön Mountains and its access to hiking and nature tourism.
-
C.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
D.
Bischofswiesen
Bischofswiesen is a municipality in the Bavarian Alps of southeastern Germany, known for its scenic mountain landscapes and proximity to Berchtesgaden.
-
E.
Reichertshofen
Reichertshofen is a market town and municipality in Upper Bavaria, Germany, known for its location near the confluence of the Paar and Ilm rivers and its proximity to the city of Ingolstadt.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d3232d48190a3c792b025c596a6 |
completed | April 10, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff2a4b0c8190a853a1f6f4d1cbaf |
completed | May 3, 2026, 7:54 a.m. |
| NEDg | Description generation | batch_69f70099f98081909877392c9ec49766 |
completed | May 3, 2026, 8 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f702620bc881909d4348fd2c709232 |
completed | May 3, 2026, 8:08 a.m. |
Created at: April 9, 2026, 9:21 p.m.