Triple
T4249933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Brienz |
E95823
|
entity |
| Predicate | hasPort |
P35
|
FINISHED |
| Object |
Bönigen
Bönigen is a Swiss village in the canton of Bern, known for its scenic location on the shore of Lake Brienz near Interlaken.
|
E444864
|
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: Bönigen | Statement: [Lake Brienz, hasPort, Bönigen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bönigen Context triple: [Lake Brienz, hasPort, Bönigen]
-
A.
Göschenen
Göschenen is a Swiss mountain village and railway junction in the canton of Uri, known as a gateway to the Gotthard region.
-
B.
Burgdorf
Burgdorf is a historic Swiss town in the canton of Bern, known for its medieval castle and role as a regional economic and cultural center.
-
C.
Muttenz
Muttenz is a municipality in northern Switzerland that serves as a major suburban and industrial center in the canton of Basel-Landschaft, adjacent to the city of Basel.
-
D.
Selzach
Selzach is a Swiss municipality located in the canton of Solothurn, known for its rural character and proximity to the Jura Mountains.
-
E.
Richterswil
Richterswil is a picturesque municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland.
- 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: Bönigen Triple: [Lake Brienz, hasPort, Bönigen]
Generated description
Bönigen is a Swiss village in the canton of Bern, known for its scenic location on the shore of Lake Brienz near Interlaken.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bönigen Target entity description: Bönigen is a Swiss village in the canton of Bern, known for its scenic location on the shore of Lake Brienz near Interlaken.
-
A.
Göschenen
Göschenen is a Swiss mountain village and railway junction in the canton of Uri, known as a gateway to the Gotthard region.
-
B.
Burgdorf
Burgdorf is a historic Swiss town in the canton of Bern, known for its medieval castle and role as a regional economic and cultural center.
-
C.
Muttenz
Muttenz is a municipality in northern Switzerland that serves as a major suburban and industrial center in the canton of Basel-Landschaft, adjacent to the city of Basel.
-
D.
Selzach
Selzach is a Swiss municipality located in the canton of Solothurn, known for its rural character and proximity to the Jura Mountains.
-
E.
Richterswil
Richterswil is a picturesque municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland.
- 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_69b3453f759881909b91f01a1e82c036 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e9f11008190a0021e0ad730a79d |
completed | March 12, 2026, 11:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b66b29cbe4819083788fe6e3e8ba3b |
completed | March 15, 2026, 8:17 a.m. |
| NEDg | Description generation | batch_69b66bec75048190979acafbb79a36e2 |
completed | March 15, 2026, 8:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b66f92f3cc8190a9dc9e931dac5378 |
completed | March 15, 2026, 8:36 a.m. |
Created at: March 12, 2026, 11:06 p.m.