Triple
T21205221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Essen |
E522558
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Schwaförden
Schwaförden is a small locality in Lower Saxony, Germany, known as a rural community within the Diepholz district.
|
E1475269
|
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: Schwaförden | Statement: [Bad Essen, hasSubdivision, Schwaförden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schwaförden Context triple: [Bad Essen, hasSubdivision, Schwaförden]
-
A.
Ödsbach
Ödsbach is a village and district of the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany, known for its scenic vineyards and Black Forest landscape.
-
B.
Heroldsbach
Heroldsbach is a small municipality in the Upper Franconia region of Bavaria, Germany, known for its rural character and local religious pilgrimage site.
-
C.
Eschwege
Eschwege is a small historic town in the German state of Hesse, known for its medieval architecture and location near the Werra River.
-
D.
Königsbach
Königsbach is a village and wine-growing district that forms part of the town of Neustadt an der Weinstraße in Rhineland-Palatinate, Germany.
-
E.
Tornesch
Tornesch is a small town in the district of Pinneberg in Schleswig-Holstein, northern Germany, known for its residential character and proximity to Hamburg.
- 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: Schwaförden Triple: [Bad Essen, hasSubdivision, Schwaförden]
Generated description
Schwaförden is a small locality in Lower Saxony, Germany, known as a rural community within the Diepholz district.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Schwaförden Target entity description: Schwaförden is a small locality in Lower Saxony, Germany, known as a rural community within the Diepholz district.
-
A.
Ödsbach
Ödsbach is a village and district of the town of Oberkirch in the Ortenau region of Baden-Württemberg, Germany, known for its scenic vineyards and Black Forest landscape.
-
B.
Heroldsbach
Heroldsbach is a small municipality in the Upper Franconia region of Bavaria, Germany, known for its rural character and local religious pilgrimage site.
-
C.
Eschwege
Eschwege is a small historic town in the German state of Hesse, known for its medieval architecture and location near the Werra River.
-
D.
Königsbach
Königsbach is a village and wine-growing district that forms part of the town of Neustadt an der Weinstraße in Rhineland-Palatinate, Germany.
-
E.
Tornesch
Tornesch is a small town in the district of Pinneberg in Schleswig-Holstein, northern Germany, known for its residential character and proximity to Hamburg.
- 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_69e0b5112d8881909510b2dcdc93106d |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e734342e9081909e241bed54dbc0b4 |
completed | April 21, 2026, 8:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a098febb9d4819093d8ae8296f658f9 |
completed | May 17, 2026, 9:52 a.m. |
| NEDg | Description generation | batch_6a0991423b288190b190b1cbf2589323 |
completed | May 17, 2026, 9:58 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09929e2ad881908e3497f9c3f2f77c |
completed | May 17, 2026, 10:04 a.m. |
Created at: April 16, 2026, 3:19 p.m.