Triple
T9684341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glâne District |
E234366
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object |
Romont
Romont is a historic Swiss town in the canton of Fribourg, known for its medieval hilltop setting and well-preserved fortifications.
|
E845371
|
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: Romont | Statement: [Glâne District, seat, Romont]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Romont Context triple: [Glâne District, seat, Romont]
-
A.
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.
-
B.
Neuchâtel
Neuchâtel is a French-speaking canton in western Switzerland known for its lakeside capital, watchmaking industry, and historic architecture.
-
C.
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.
-
D.
Romont SO
Romont SO is a small municipality in the canton of Solothurn in northwestern Switzerland.
-
E.
Stettlen
Stettlen is a municipality in the canton of Bern in Switzerland, situated just east of the city of Bern and functioning largely as a residential and commuter community.
- 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: Romont Triple: [Glâne District, seat, Romont]
Generated description
Romont is a historic Swiss town in the canton of Fribourg, known for its medieval hilltop setting and well-preserved fortifications.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Romont Target entity description: Romont is a historic Swiss town in the canton of Fribourg, known for its medieval hilltop setting and well-preserved fortifications.
-
A.
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.
-
B.
Neuchâtel
Neuchâtel is a French-speaking canton in western Switzerland known for its lakeside capital, watchmaking industry, and historic architecture.
-
C.
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.
-
D.
Romont SO
Romont SO is a small municipality in the canton of Solothurn in northwestern Switzerland.
-
E.
Stettlen
Stettlen is a municipality in the canton of Bern in Switzerland, situated just east of the city of Bern and functioning largely as a residential and commuter community.
- 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_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_69d2ffd03dac81909f6c91afb8d49521 |
completed | April 6, 2026, 12:35 a.m. |
| NEDg | Description generation | batch_69d301dd614481909b357f319ba5e876 |
completed | April 6, 2026, 12:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d302978e808190a9f5371a2bf4abce |
completed | April 6, 2026, 12:47 a.m. |
Created at: March 30, 2026, 8:16 p.m.