Triple
T6331873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niederbipp |
E142398
|
entity |
| Predicate | hasNeighboringMunicipality |
P224
|
FINISHED |
| Object |
Schwarzhäusern
Schwarzhäusern is a small municipality in the canton of Bern in Switzerland, situated in the Oberaargau region.
|
E585771
|
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: Schwarzhäusern | Statement: [Niederbipp, hasNeighboringMunicipality, Schwarzhäusern]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schwarzhäusern Context triple: [Niederbipp, hasNeighboringMunicipality, Schwarzhäusern]
-
A.
Schwartzerdt
Schwartzerdt is the original German surname of the 16th-century Protestant reformer and humanist Philip Melanchthon, which he later Hellenized into the name by which he is best known.
-
B.
Bad Rothenfelde
Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
-
C.
Schwarz
Schwarz is a theoretical physicist best known as one of the pioneers of string theory and for his work on anomaly cancellation.
-
D.
Schwaz
Schwaz is a historic silver-mining town in the Austrian state of Tyrol, known for its medieval center and alpine setting.
-
E.
Bad Godesberg
Bad Godesberg is a district in the city of Bonn, Germany, known for its affluent residential areas, former diplomatic missions, and scenic location along the Rhine River.
- 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: Schwarzhäusern Triple: [Niederbipp, hasNeighboringMunicipality, Schwarzhäusern]
Generated description
Schwarzhäusern is a small municipality in the canton of Bern in Switzerland, situated in the Oberaargau region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Schwarzhäusern Target entity description: Schwarzhäusern is a small municipality in the canton of Bern in Switzerland, situated in the Oberaargau region.
-
A.
Schwartzerdt
Schwartzerdt is the original German surname of the 16th-century Protestant reformer and humanist Philip Melanchthon, which he later Hellenized into the name by which he is best known.
-
B.
Bad Rothenfelde
Bad Rothenfelde is a spa town in Lower Saxony, Germany, known for its saline springs and health resort facilities.
-
C.
Schwarz
Schwarz is a theoretical physicist best known as one of the pioneers of string theory and for his work on anomaly cancellation.
-
D.
Schwaz
Schwaz is a historic silver-mining town in the Austrian state of Tyrol, known for its medieval center and alpine setting.
-
E.
Bad Godesberg
Bad Godesberg is a district in the city of Bonn, Germany, known for its affluent residential areas, former diplomatic missions, and scenic location along the Rhine River.
- 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_69c008d4d8e88190ad301c05b08722ac |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0651634b08190b54860ba0a70f5c4 |
completed | March 22, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6041f713c8190b27ba54181049377 |
completed | March 27, 2026, 4:14 a.m. |
| NEDg | Description generation | batch_69c604d3839081909f98c37f0fe8f0af |
completed | March 27, 2026, 4:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6054d2e388190a4bafffce879b039 |
completed | March 27, 2026, 4:19 a.m. |
Created at: March 22, 2026, 4:30 p.m.