Triple
T13255274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kelkheim |
E315641
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Münster (Kelkheim)
Münster (Kelkheim) is a district of the town of Kelkheim in the Main-Taunus-Kreis region of Hesse, Germany.
|
E1030502
|
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: Münster (Kelkheim) | Statement: [Kelkheim, hasSubdivision, Münster (Kelkheim)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Münster (Kelkheim) Context triple: [Kelkheim, hasSubdivision, Münster (Kelkheim)]
-
A.
Münster (Hesse)
Münster (Hesse) is a small municipality in the German state of Hesse, located in the Darmstadt-Dieburg district in the southern part of the state.
-
B.
Münster-Geschinen
Münster-Geschinen is a small alpine village in the Swiss canton of Valais, known for its traditional wooden houses and location in the upper Rhone valley.
-
C.
Minschter
Minschter is the Alsatian name for the city of Munster in the Alsace region of France.
-
D.
Mainz-Kostheim
Mainz-Kostheim is a district of the city of Wiesbaden in Germany, located at the confluence of the Main and Rhine rivers opposite the city of Mainz.
-
E.
Münster
Münster is a historic city in western Germany known as one of the principal sites where the Peace of Westphalia treaties were negotiated and signed, ending the Thirty Years' War in 1648.
- 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: Münster (Kelkheim) Triple: [Kelkheim, hasSubdivision, Münster (Kelkheim)]
Generated description
Münster (Kelkheim) is a district of the town of Kelkheim in the Main-Taunus-Kreis region of Hesse, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Münster (Kelkheim) Target entity description: Münster (Kelkheim) is a district of the town of Kelkheim in the Main-Taunus-Kreis region of Hesse, Germany.
-
A.
Münster (Hesse)
Münster (Hesse) is a small municipality in the German state of Hesse, located in the Darmstadt-Dieburg district in the southern part of the state.
-
B.
Münster-Geschinen
Münster-Geschinen is a small alpine village in the Swiss canton of Valais, known for its traditional wooden houses and location in the upper Rhone valley.
-
C.
Minschter
Minschter is the Alsatian name for the city of Munster in the Alsace region of France.
-
D.
Mainz-Kostheim
Mainz-Kostheim is a district of the city of Wiesbaden in Germany, located at the confluence of the Main and Rhine rivers opposite the city of Mainz.
-
E.
Münster
Münster is a historic city in western Germany known as one of the principal sites where the Peace of Westphalia treaties were negotiated and signed, ending the Thirty Years' War in 1648.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98f7517048190b4eac4e44e81ff66 |
completed | April 11, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f70a4240d881909f0ee898fd272826 |
completed | May 3, 2026, 8:41 a.m. |
| NEDg | Description generation | batch_69f70c9718d08190b09fc6723712ef55 |
completed | May 3, 2026, 8:51 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f70d32b38881909d500b81a0164bda |
completed | May 3, 2026, 8:54 a.m. |
Created at: April 9, 2026, 9:24 p.m.