Triple
T5392842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kammersrohr |
E120374
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object |
Lüsslingen
Lüsslingen is a village and former municipality in the canton of Solothurn in Switzerland.
|
E525223
|
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: Lüsslingen | Statement: [Kammersrohr, hasNeighboringMunicipality, Lüsslingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lüsslingen Context triple: [Kammersrohr, hasNeighboringMunicipality, Lüsslingen]
-
A.
Steißlingen
Steißlingen is a municipality in the district of Konstanz in the state of Baden-Württemberg in southern Germany.
-
B.
Niederbühl
Niederbühl is a district of the town of Rastatt in the state of Baden-Württemberg in southwestern Germany.
-
C.
Andelfingen
Andelfingen is a municipality and regional center in the canton of Zürich in northern Switzerland, known for its rural character and vineyards along the Thur River.
-
D.
Göschenen
Göschenen is a Swiss mountain village and railway junction in the canton of Uri, known as a gateway to the Gotthard region.
-
E.
Wädenswil
Wädenswil is a Swiss town in the canton of Zurich known for its lakeside location, wine-growing tradition, and research institutes.
- 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: Lüsslingen Triple: [Kammersrohr, hasNeighboringMunicipality, Lüsslingen]
Generated description
Lüsslingen is a village and former municipality in the canton of Solothurn in Switzerland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lüsslingen Target entity description: Lüsslingen is a village and former municipality in the canton of Solothurn in Switzerland.
-
A.
Steißlingen
Steißlingen is a municipality in the district of Konstanz in the state of Baden-Württemberg in southern Germany.
-
B.
Niederbühl
Niederbühl is a district of the town of Rastatt in the state of Baden-Württemberg in southwestern Germany.
-
C.
Andelfingen
Andelfingen is a municipality and regional center in the canton of Zürich in northern Switzerland, known for its rural character and vineyards along the Thur River.
-
D.
Göschenen
Göschenen is a Swiss mountain village and railway junction in the canton of Uri, known as a gateway to the Gotthard region.
-
E.
Wädenswil
Wädenswil is a Swiss town in the canton of Zurich known for its lakeside location, wine-growing tradition, and research institutes.
- 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_69bd46354c648190a38b26f107010a96 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd871b81d08190993928e2c6251226 |
completed | March 20, 2026, 5:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf88e4ebe48190bf1d8643149a88f0 |
completed | March 22, 2026, 6:15 a.m. |
| NEDg | Description generation | batch_69bf895a03908190a822e021c50bb797 |
completed | March 22, 2026, 6:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf89ef2fe08190a6696459fab68a79 |
completed | March 22, 2026, 6:19 a.m. |
Created at: March 20, 2026, 2:04 p.m.