Triple
T14760573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Burgäschi |
E346848
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
Herzogenbuchsee
Herzogenbuchsee is a municipality in the canton of Bern in Switzerland, known as a regional center in the Oberaargau area.
|
E1124321
|
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: Herzogenbuchsee | Statement: [Lake Burgäschi, locatedNear, Herzogenbuchsee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Herzogenbuchsee Context triple: [Lake Burgäschi, locatedNear, Herzogenbuchsee]
-
A.
Münchenbuchsee
Münchenbuchsee is a municipality in the canton of Bern, Switzerland, known as the birthplace of the influential modernist painter Paul Klee.
-
B.
Fennsee
Fennsee is a small urban lake and surrounding green area in Berlin’s Wilmersdorf district, popular for local recreation and walking.
-
C.
Gerzensee
Gerzensee is a small municipality in the canton of Bern, Switzerland, known for its scenic lake and rural alpine surroundings.
-
D.
Schlosssee
Schlosssee is a scenic lake in the spa town of Bad Waldsee in southern Germany, known for recreation and its picturesque natural setting.
-
E.
Hallwilersee
Hallwilersee is a scenic lake in the Swiss cantons of Aargau and Lucerne, popular for recreation, boating, and nature conservation.
- 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: Herzogenbuchsee Triple: [Lake Burgäschi, locatedNear, Herzogenbuchsee]
Generated description
Herzogenbuchsee is a municipality in the canton of Bern in Switzerland, known as a regional center in the Oberaargau area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Herzogenbuchsee Target entity description: Herzogenbuchsee is a municipality in the canton of Bern in Switzerland, known as a regional center in the Oberaargau area.
-
A.
Münchenbuchsee
Münchenbuchsee is a municipality in the canton of Bern, Switzerland, known as the birthplace of the influential modernist painter Paul Klee.
-
B.
Fennsee
Fennsee is a small urban lake and surrounding green area in Berlin’s Wilmersdorf district, popular for local recreation and walking.
-
C.
Gerzensee
Gerzensee is a small municipality in the canton of Bern, Switzerland, known for its scenic lake and rural alpine surroundings.
-
D.
Schlosssee
Schlosssee is a scenic lake in the spa town of Bad Waldsee in southern Germany, known for recreation and its picturesque natural setting.
-
E.
Hallwilersee
Hallwilersee is a scenic lake in the Swiss cantons of Aargau and Lucerne, popular for recreation, boating, and nature conservation.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7f207dc819088a53f717736a121 |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe64f0d948819080cc759ca599503d |
completed | May 8, 2026, 10:34 p.m. |
| NEDg | Description generation | batch_69fe6713714481909a2ac056853ef67d |
completed | May 8, 2026, 10:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe677248b08190a7d8dcaed116e307 |
completed | May 8, 2026, 10:45 p.m. |
Created at: April 10, 2026, 1:30 a.m.