Triple
T20961037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Wildungen |
E516243
|
entity |
| Predicate | hasCityPart |
P12399
|
FINISHED |
| Object |
Hüddingen
Hüddingen is a small district or village that forms part of the spa town of Bad Wildungen in the state of Hesse, Germany.
|
E1461505
|
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: Hüddingen | Statement: [Bad Wildungen, hasCityPart, Hüddingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hüddingen Context triple: [Bad Wildungen, hasCityPart, Hüddingen]
-
A.
Höttingen
Höttingen is a small rural municipality in the Weißenburg-Gunzenhausen district of Bavaria in southern Germany.
-
B.
Deggingen
Deggingen is a small municipality in the German state of Baden-Württemberg, situated in the Swabian Jura and known for its scenic valley setting along the Fils River.
-
C.
Hünstetten
Hünstetten is a municipality in the Rheingau-Taunus district of the German state of Hesse, known for its rural character and proximity to the Taunus hills.
-
D.
Gündlingen
Gündlingen is a village and district of the town Breisach am Rhein in the state of Baden-Württemberg in southwestern Germany.
-
E.
Nüdlingen
Nüdlingen is a municipality in northern Bavaria, Germany, situated in the Franconian Saale region near the spa town of Bad Kissingen.
- 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: Hüddingen Triple: [Bad Wildungen, hasCityPart, Hüddingen]
Generated description
Hüddingen is a small district or village that forms part of the spa town of Bad Wildungen in the state of Hesse, Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hüddingen Target entity description: Hüddingen is a small district or village that forms part of the spa town of Bad Wildungen in the state of Hesse, Germany.
-
A.
Höttingen
Höttingen is a small rural municipality in the Weißenburg-Gunzenhausen district of Bavaria in southern Germany.
-
B.
Deggingen
Deggingen is a small municipality in the German state of Baden-Württemberg, situated in the Swabian Jura and known for its scenic valley setting along the Fils River.
-
C.
Hünstetten
Hünstetten is a municipality in the Rheingau-Taunus district of the German state of Hesse, known for its rural character and proximity to the Taunus hills.
-
D.
Gündlingen
Gündlingen is a village and district of the town Breisach am Rhein in the state of Baden-Württemberg in southwestern Germany.
-
E.
Nüdlingen
Nüdlingen is a municipality in northern Bavaria, Germany, situated in the Franconian Saale region near the spa town of Bad Kissingen.
- 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_69e0b4fde6c48190af1398e7e734629e |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fb6f134081908b1ed48ce708f3d5 |
completed | April 21, 2026, 4:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a093b4802a48190906e370603fafef0 |
completed | May 17, 2026, 3:51 a.m. |
| NEDg | Description generation | batch_6a093c737a34819081fb6eb74742d6bf |
completed | May 17, 2026, 3:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a093d0ce9ac8190ba54d6bef0b5bcc3 |
completed | May 17, 2026, 3:59 a.m. |
Created at: April 16, 2026, 1:31 p.m.