Triple
T10988268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhön-Grabfeld |
E259686
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Bad Königshofen im Grabfeld
Bad Königshofen im Grabfeld is a small spa town in northern Bavaria, Germany, known for its thermal baths and location near the Rhön hills.
|
E898339
|
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: Bad Königshofen im Grabfeld | Statement: [Rhön-Grabfeld, contains, Bad Königshofen im Grabfeld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bad Königshofen im Grabfeld Context triple: [Rhön-Grabfeld, contains, Bad Königshofen im Grabfeld]
-
A.
Bad Rothenfelde
Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
-
B.
Bad Harzburg
Bad Harzburg is a German spa and resort town on the northern edge of the Harz Mountains, known for its thermal baths, hiking trails, and historic castle ruins.
-
C.
Dinkelscherben
Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
-
D.
Schöffengrund
Schöffengrund is a rural municipality in the Lahn-Dill district of the German state of Hesse.
-
E.
Bad Staffelstein
Bad Staffelstein is a small Bavarian town in Germany known for its historic architecture, spa culture, and nearby pilgrimage sites.
- 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: Bad Königshofen im Grabfeld Triple: [Rhön-Grabfeld, contains, Bad Königshofen im Grabfeld]
Generated description
Bad Königshofen im Grabfeld is a small spa town in northern Bavaria, Germany, known for its thermal baths and location near the Rhön hills.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bad Königshofen im Grabfeld Target entity description: Bad Königshofen im Grabfeld is a small spa town in northern Bavaria, Germany, known for its thermal baths and location near the Rhön hills.
-
A.
Bad Rothenfelde
Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
-
B.
Bad Harzburg
Bad Harzburg is a German spa and resort town on the northern edge of the Harz Mountains, known for its thermal baths, hiking trails, and historic castle ruins.
-
C.
Dinkelscherben
Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
-
D.
Schöffengrund
Schöffengrund is a rural municipality in the Lahn-Dill district of the German state of Hesse.
-
E.
Bad Staffelstein
Bad Staffelstein is a small Bavarian town in Germany known for its historic architecture, spa culture, and nearby pilgrimage sites.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d787b574d08190adec34b814a26437 |
completed | April 9, 2026, 11:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e344f95ab88190bbce8f0eab0b2713 |
completed | April 18, 2026, 8:46 a.m. |
| NEDg | Description generation | batch_69e3556e8b408190a02a1fe194ae5750 |
completed | April 18, 2026, 9:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3591ecd548190b049ce95fe3f86d9 |
completed | April 18, 2026, 10:12 a.m. |
Created at: April 8, 2026, 9:24 p.m.