Triple
T9684342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glâne District |
E234366
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object | Romont |
E845371
|
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: Romont | Statement: [Glâne District, containsMunicipality, Romont]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Romont Context triple: [Glâne District, containsMunicipality, Romont]
-
A.
Romont
chosen
Romont is a historic Swiss town in the canton of Fribourg, known for its medieval hilltop setting and well-preserved fortifications.
-
B.
Lausanne
Lausanne is a major Swiss city on the shores of Lake Geneva, known for hosting the International Olympic Committee and its vibrant cultural and academic institutions.
-
C.
Neuchâtel
Neuchâtel is a French-speaking canton in western Switzerland known for its lakeside capital, watchmaking industry, and historic architecture.
-
D.
Nyon
Nyon is a Swiss town on the shores of Lake Geneva that serves as the administrative home of several major sports organizations, including UEFA.
-
E.
Romont SO
Romont SO is a small municipality in the canton of Solothurn in northwestern Switzerland.
- 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_69ca84c99e34819092e5563a7106cfca |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9ccf21a08190a1302b933b9e50be |
completed | April 1, 2026, 10:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3170e01408190969fdd8c366f9276 |
completed | April 6, 2026, 2:14 a.m. |
Created at: March 30, 2026, 8:16 p.m.