Triple
T17050199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lauda-Königshofen |
E413673
|
entity |
| Predicate | hasCityPart |
P12399
|
FINISHED |
| Object |
Königshofen
Königshofen is a district of the town Lauda-Königshofen in the Main-Tauber region of Baden-Württemberg, Germany.
|
E1275951
|
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: Königshofen | Statement: [Lauda-Königshofen, hasCityPart, Königshofen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Königshofen Context triple: [Lauda-Königshofen, hasCityPart, Königshofen]
-
A.
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.
-
B.
Gerolzhofen
Gerolzhofen is a small historic town in northern Bavaria, Germany, known for its medieval architecture and wine-growing surroundings.
-
C.
Gersthofen
Gersthofen is a town in Bavaria, Germany, located just north of Augsburg and known for its industrial presence and role as a regional transport hub.
-
D.
Odelshofen
Odelshofen is a village and district (Ortsteil) of the town of Kehl in the state of Baden-Württemberg, Germany.
-
E.
Wehofen
Wehofen is a district of the Walsum area in the city of Duisburg in North Rhine-Westphalia, 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: Königshofen Triple: [Lauda-Königshofen, hasCityPart, Königshofen]
Generated description
Königshofen is a district of the town Lauda-Königshofen in the Main-Tauber region of Baden-Württemberg, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Königshofen Target entity description: Königshofen is a district of the town Lauda-Königshofen in the Main-Tauber region of Baden-Württemberg, Germany.
-
A.
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.
-
B.
Gerolzhofen
Gerolzhofen is a small historic town in northern Bavaria, Germany, known for its medieval architecture and wine-growing surroundings.
-
C.
Gersthofen
Gersthofen is a town in Bavaria, Germany, located just north of Augsburg and known for its industrial presence and role as a regional transport hub.
-
D.
Odelshofen
Odelshofen is a village and district (Ortsteil) of the town of Kehl in the state of Baden-Württemberg, Germany.
-
E.
Wehofen
Wehofen is a district of the Walsum area in the city of Duisburg in North Rhine-Westphalia, 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3daa1aeac81909e8d97bd708c6b71 |
completed | April 18, 2026, 7:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01d273f37c8190bbad1ee6a0dc215f |
completed | May 11, 2026, 12:58 p.m. |
| NEDg | Description generation | batch_6a01d89932cc8190b3fd0ee72567cf46 |
completed | May 11, 2026, 1:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01d9741c348190ab926699e1b6a48f |
completed | May 11, 2026, 1:28 p.m. |
Created at: April 10, 2026, 5:34 a.m.