Triple
T7102905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilseder Berg |
E165502
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object |
Bispingen
Bispingen is a municipality in Lower Saxony, Germany, known as a gateway to the Lüneburg Heath nature reserve and its surrounding scenic landscapes.
|
E642366
|
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: Bispingen | Statement: [Wilseder Berg, near, Bispingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bispingen Context triple: [Wilseder Berg, near, Bispingen]
-
A.
Briesen
Briesen is a small town in present-day Germany best known as the birthplace of Nobel Prize–winning chemist Walther Nernst.
-
B.
Böbing
Böbing is a small municipality in the Weilheim-Schongau district of Bavaria, Germany, known for its rural setting in the Alpine foothills.
-
C.
Bissingen
Bissingen is a suburb of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
-
D.
Bermaringen
Bermaringen is a village and district within the municipality of Blaustein in the Alb-Donau region of Baden-Württemberg, Germany.
-
E.
Wippingen
Wippingen is a village and district (Ortsteil) of the municipality of Blaustein in the Alb-Donau district of Baden-Württemberg, Germany.
- 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: Bispingen Triple: [Wilseder Berg, near, Bispingen]
Generated description
Bispingen is a municipality in Lower Saxony, Germany, known as a gateway to the Lüneburg Heath nature reserve and its surrounding scenic landscapes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bispingen Target entity description: Bispingen is a municipality in Lower Saxony, Germany, known as a gateway to the Lüneburg Heath nature reserve and its surrounding scenic landscapes.
-
A.
Briesen
Briesen is a small town in present-day Germany best known as the birthplace of Nobel Prize–winning chemist Walther Nernst.
-
B.
Böbing
Böbing is a small municipality in the Weilheim-Schongau district of Bavaria, Germany, known for its rural setting in the Alpine foothills.
-
C.
Bissingen
Bissingen is a suburb of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
-
D.
Bermaringen
Bermaringen is a village and district within the municipality of Blaustein in the Alb-Donau region of Baden-Württemberg, Germany.
-
E.
Wippingen
Wippingen is a village and district (Ortsteil) of the municipality of Blaustein in the Alb-Donau district of Baden-Württemberg, Germany.
- 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_69c6887fcddc8190a5d58908f6dee590 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e58a0a2c819088e0c8874fb4491f |
completed | March 27, 2026, 8:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c79cad60788190bb2b17d1c3f8e1cc |
completed | March 28, 2026, 9:17 a.m. |
| NEDg | Description generation | batch_69c79d72dd70819084a4bf7e72865ed9 |
completed | March 28, 2026, 9:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c79e12a40c8190b21128e17c3e212e |
completed | March 28, 2026, 9:23 a.m. |
Created at: March 27, 2026, 2:42 p.m.