Triple
T17050201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lauda-Königshofen |
E413673
|
entity |
| Predicate | hasCityPart |
P12399
|
FINISHED |
| Object |
Gerlachsheim
Gerlachsheim is a district of the town Lauda-Königshofen in the Main-Tauber-Kreis region of Baden-Württemberg, Germany.
|
E1276652
|
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: Gerlachsheim | Statement: [Lauda-Königshofen, hasCityPart, Gerlachsheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gerlachsheim Context triple: [Lauda-Königshofen, hasCityPart, Gerlachsheim]
-
A.
Grafenrheinfeld
Grafenrheinfeld is a small Bavarian town best known for hosting the former Grafenrheinfeld nuclear power plant on the Main River in northern Germany.
-
B.
Höchheim
Höchheim is a small municipality in the Rhön-Grabfeld district of northern Bavaria, Germany.
-
C.
Odelzhausen
Odelzhausen is a municipality in Bavaria, Germany, known for its historic castle and location along the Autobahn between Munich and Augsburg.
-
D.
Schwabhausen
Schwabhausen is a municipality in Bavaria, Germany, known for its rural character and location within the greater Munich metropolitan region.
-
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: Gerlachsheim Triple: [Lauda-Königshofen, hasCityPart, Gerlachsheim]
Generated description
Gerlachsheim is a district of the town Lauda-Königshofen in the Main-Tauber-Kreis region of Baden-Württemberg, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gerlachsheim Target entity description: Gerlachsheim is a district of the town Lauda-Königshofen in the Main-Tauber-Kreis region of Baden-Württemberg, Germany.
-
A.
Grafenrheinfeld
Grafenrheinfeld is a small Bavarian town best known for hosting the former Grafenrheinfeld nuclear power plant on the Main River in northern Germany.
-
B.
Höchheim
Höchheim is a small municipality in the Rhön-Grabfeld district of northern Bavaria, Germany.
-
C.
Odelzhausen
Odelzhausen is a municipality in Bavaria, Germany, known for its historic castle and location along the Autobahn between Munich and Augsburg.
-
D.
Schwabhausen
Schwabhausen is a municipality in Bavaria, Germany, known for its rural character and location within the greater Munich metropolitan region.
-
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_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_6a01ddcf76fc81908b455c570e12d4d8 |
completed | May 11, 2026, 1:46 p.m. |
| NEDg | Description generation | batch_6a01df83eae88190b8203169c73affb1 |
completed | May 11, 2026, 1:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01dfbfc47881908fc933be12de619d |
completed | May 11, 2026, 1:55 p.m. |
Created at: April 10, 2026, 5:34 a.m.