Triple
T16460251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wohlen bei Bern |
E399786
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Murzelen
Murzelen is a small village and locality within the municipality of Wohlen bei Bern in the canton of Bern, Switzerland.
|
E1214859
|
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: Murzelen | Statement: [Wohlen bei Bern, hasPart, Murzelen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Murzelen Context triple: [Wohlen bei Bern, hasPart, Murzelen]
-
A.
Maleny
Maleny is a scenic rural town in the Sunshine Coast hinterland of Queensland, Australia, known for its lush rolling hills, dairy farms, arts community, and panoramic views over the Glass House Mountains.
-
B.
Rózsadomb
Rózsadomb is an affluent, villa-filled hillside neighborhood in Budapest known for its panoramic views over the city and the Danube.
-
C.
Hagetmau
Hagetmau is a small town in southwestern France’s Landes department, known for its rural character and traditional Gascon culture.
-
D.
Ziegenberg
Ziegenberg is a locality in Hesse, Germany, historically notable for its role and nearby military installations during the later years of World War II.
-
E.
Semmerzake
Semmerzake is a village in East Flanders, Belgium, known for its rural character and former military airfield.
- 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: Murzelen Triple: [Wohlen bei Bern, hasPart, Murzelen]
Generated description
Murzelen is a small village and locality within the municipality of Wohlen bei Bern in the canton of Bern, Switzerland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Murzelen Target entity description: Murzelen is a small village and locality within the municipality of Wohlen bei Bern in the canton of Bern, Switzerland.
-
A.
Maleny
Maleny is a scenic rural town in the Sunshine Coast hinterland of Queensland, Australia, known for its lush rolling hills, dairy farms, arts community, and panoramic views over the Glass House Mountains.
-
B.
Rózsadomb
Rózsadomb is an affluent, villa-filled hillside neighborhood in Budapest known for its panoramic views over the city and the Danube.
-
C.
Hagetmau
Hagetmau is a small town in southwestern France’s Landes department, known for its rural character and traditional Gascon culture.
-
D.
Ziegenberg
Ziegenberg is a locality in Hesse, Germany, historically notable for its role and nearby military installations during the later years of World War II.
-
E.
Semmerzake
Semmerzake is a village in East Flanders, Belgium, known for its rural character and former military airfield.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32d80e66c8190b2b3199efe9cfaa1 |
completed | April 18, 2026, 7:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f53aff081909a75de6672f15f0e |
completed | May 10, 2026, 9:26 a.m. |
| NEDg | Description generation | batch_6a0050a0f5b081908417c6062b1f50cc |
completed | May 10, 2026, 9:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00517b7b1c819098118fdbe03eb010 |
completed | May 10, 2026, 9:35 a.m. |
Created at: April 10, 2026, 5:10 a.m.