Triple
T19325468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syrgenstein |
E483334
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Landshausen
Landshausen is a village-level subdivision of the municipality of Syrgenstein in the Bavarian district of Dillingen, Germany.
|
E1375532
|
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: Landshausen | Statement: [Syrgenstein, hasSubdivision, Landshausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Landshausen Context triple: [Syrgenstein, hasSubdivision, Landshausen]
-
A.
Leutershausen
Leutershausen is a historic small town in Bavaria, Germany, known for its well-preserved medieval character and traditional Franconian architecture.
-
B.
Helmarshausen
Helmarshausen is a historic district of the spa town Bad Karlshafen in northern Hesse, Germany, known for its medieval heritage and former Benedictine monastery.
-
C.
Altshausen
Altshausen is a small historic town in the German state of Baden-Württemberg, known for its former ducal residence and picturesque setting in Upper Swabia.
-
D.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
E.
Ziemetshausen
Ziemetshausen is a small municipality in the Swabian region of Bavaria 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: Landshausen Triple: [Syrgenstein, hasSubdivision, Landshausen]
Generated description
Landshausen is a village-level subdivision of the municipality of Syrgenstein in the Bavarian district of Dillingen, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Landshausen Target entity description: Landshausen is a village-level subdivision of the municipality of Syrgenstein in the Bavarian district of Dillingen, Germany.
-
A.
Leutershausen
Leutershausen is a historic small town in Bavaria, Germany, known for its well-preserved medieval character and traditional Franconian architecture.
-
B.
Helmarshausen
Helmarshausen is a historic district of the spa town Bad Karlshafen in northern Hesse, Germany, known for its medieval heritage and former Benedictine monastery.
-
C.
Altshausen
Altshausen is a small historic town in the German state of Baden-Württemberg, known for its former ducal residence and picturesque setting in Upper Swabia.
-
D.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
E.
Ziemetshausen
Ziemetshausen is a small municipality in the Swabian region of Bavaria 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e60d8bb28c81909b3a3bbb96b69b4f |
completed | April 20, 2026, 11:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0733bdfab4819098d0942bfc19a71c |
completed | May 15, 2026, 2:54 p.m. |
| NEDg | Description generation | batch_6a073576a390819093aad12ca37a9ece |
completed | May 15, 2026, 3:02 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0735d2d2588190b196c41a9d251e2e |
completed | May 15, 2026, 3:03 p.m. |
Created at: April 10, 2026, 1:33 p.m.