Triple
T9164268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weißenfels district |
E219906
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Reichardtswerben
Reichardtswerben is a small municipality in the Weißenfels area of Saxony-Anhalt in eastern Germany.
|
E782916
|
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: Reichardtswerben | Statement: [Weißenfels district, hasMunicipality, Reichardtswerben]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reichardtswerben Context triple: [Weißenfels district, hasMunicipality, Reichardtswerben]
-
A.
Wurmberg
Wurmberg is a prominent mountain in the Harz range of central Germany, popular for skiing, hiking, and panoramic views.
-
B.
Zollikofen
Zollikofen is a municipality in the canton of Bern in Switzerland, functioning as a suburban community within the greater Bern metropolitan region.
-
C.
Seckbach
Seckbach is a district in the east of Frankfurt am Main, Germany, known for its residential character and proximity to green spaces like the Lohrberg.
-
D.
Röthlein
Röthlein is a small municipality in the Schweinfurt district of Bavaria, Germany.
-
E.
Mossenberg-Wöhren
Mossenberg-Wöhren is a small village in North Rhine-Westphalia, Germany, known primarily as the birthplace of former German chancellor Gerhard Schröder.
- 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: Reichardtswerben Triple: [Weißenfels district, hasMunicipality, Reichardtswerben]
Generated description
Reichardtswerben is a small municipality in the Weißenfels area of Saxony-Anhalt in eastern Germany.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Reichardtswerben Target entity description: Reichardtswerben is a small municipality in the Weißenfels area of Saxony-Anhalt in eastern Germany.
-
A.
Wurmberg
Wurmberg is a prominent mountain in the Harz range of central Germany, popular for skiing, hiking, and panoramic views.
-
B.
Zollikofen
Zollikofen is a municipality in the canton of Bern in Switzerland, functioning as a suburban community within the greater Bern metropolitan region.
-
C.
Seckbach
Seckbach is a district in the east of Frankfurt am Main, Germany, known for its residential character and proximity to green spaces like the Lohrberg.
-
D.
Röthlein
Röthlein is a small municipality in the Schweinfurt district of Bavaria, Germany.
-
E.
Mossenberg-Wöhren
Mossenberg-Wöhren is a small village in North Rhine-Westphalia, Germany, known primarily as the birthplace of former German chancellor Gerhard Schröder.
- 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_69ca83e3633c81908688a9fa2306ba99 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaa2ee64c8190a9a5abafe5d0b086 |
completed | April 1, 2026, 5:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0547df750819095853f21cf740c63 |
completed | April 3, 2026, 11:59 p.m. |
| NEDg | Description generation | batch_69d0554fda40819083ef2d13d6fba905 |
completed | April 4, 2026, 12:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d055ca4fc08190b30e1b31ded51189 |
completed | April 4, 2026, 12:05 a.m. |
Created at: March 30, 2026, 7:21 p.m.