Triple
T13343480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Administrative District of Biel/Bienne |
E317885
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Nidau
Nidau is a small Swiss town in the canton of Bern, situated near Lake Biel and known for its historic old town and role as a local administrative center.
|
E1046886
|
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: Nidau | Statement: [Administrative District of Biel/Bienne, contains, Nidau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nidau Context triple: [Administrative District of Biel/Bienne, contains, Nidau]
-
A.
Nideggen
Nideggen is a historic town in North Rhine-Westphalia, Germany, known for its medieval castle and scenic location in the Eifel region.
-
B.
Neuenegg
Neuenegg is a Swiss municipality in the canton of Bern, known for its rural character and location near the city of Bern.
-
C.
Attiswil
Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
-
D.
Worb
Worb is a municipality in the canton of Bern in Switzerland, known for its historic village center and proximity to the city of Bern.
-
E.
Sursee
Sursee is a historic Swiss town in the canton of Lucerne, known for its well-preserved medieval old town and scenic setting near Lake Sempach.
- 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: Nidau Triple: [Administrative District of Biel/Bienne, contains, Nidau]
Generated description
Nidau is a small Swiss town in the canton of Bern, situated near Lake Biel and known for its historic old town and role as a local administrative center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nidau Target entity description: Nidau is a small Swiss town in the canton of Bern, situated near Lake Biel and known for its historic old town and role as a local administrative center.
-
A.
Nideggen
Nideggen is a historic town in North Rhine-Westphalia, Germany, known for its medieval castle and scenic location in the Eifel region.
-
B.
Neuenegg
Neuenegg is a Swiss municipality in the canton of Bern, known for its rural character and location near the city of Bern.
-
C.
Attiswil
Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
-
D.
Worb
Worb is a municipality in the canton of Bern in Switzerland, known for its historic village center and proximity to the city of Bern.
-
E.
Sursee
Sursee is a historic Swiss town in the canton of Lucerne, known for its well-preserved medieval old town and scenic setting near Lake Sempach.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8839b48190b164414b418e756c |
completed | April 11, 2026, 1:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75d8322ac8190a9830d9ca92f455f |
completed | May 3, 2026, 2:36 p.m. |
| NEDg | Description generation | batch_69f75f4352d48190ab57ab8ee57dba13 |
completed | May 3, 2026, 2:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f75f9fced081909962a881e469d3c4 |
completed | May 3, 2026, 2:45 p.m. |
Created at: April 9, 2026, 9:31 p.m.