Triple
T7270153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delémont |
E161079
|
entity |
| Predicate | twinTown |
P1072
|
FINISHED |
| Object | Burgdorf |
E401058
|
NE FINISHED |
How this triple was built (2 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: Burgdorf | Statement: [Delémont, twinTown, Burgdorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Burgdorf Context triple: [Delémont, twinTown, Burgdorf]
-
A.
Burgdorf
chosen
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.
-
B.
Bremgarten
Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
-
C.
Aarburg
Aarburg is a historic Swiss town in the canton of Aargau, known for its prominent riverside fortress overlooking the Aare River.
-
D.
Bönigen
Bönigen is a Swiss village in the canton of Bern, known for its scenic location on the shore of Lake Brienz near Interlaken.
-
E.
Neuenegg
Neuenegg is a Swiss municipality in the canton of Bern, known for its rural character and location near the city of Bern.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c6885181008190b419040e22939c7c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eae9f8bc8190a8c31cc29926919c |
completed | March 27, 2026, 8:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7eed8c5448190b83faee62f8122de |
completed | March 28, 2026, 3:08 p.m. |
Created at: March 27, 2026, 2:58 p.m.