Triple
T20940136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avenches |
E515695
|
entity |
| Predicate | hasNearbyCity |
P350
|
FINISHED |
| Object | Murten |
—
|
NE NERFINISHED |
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: Murten | Statement: [Avenches, hasNearbyCity, Murten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Murten Context triple: [Avenches, hasNearbyCity, Murten]
-
A.
Murten
chosen
Murten is a historic bilingual town in the canton of Fribourg, Switzerland, known for its well-preserved medieval old town and lakeside setting on Lake Murten.
-
B.
Boniswil
Boniswil is a small municipality in the canton of Aargau in northern Switzerland, situated near Lake Hallwil and known for its rural character.
-
C.
Grenchen
Grenchen is a Swiss town in the canton of Solothurn known for its watchmaking industry and location at the foot of the Jura Mountains.
-
D.
Regensdorf
Regensdorf is a municipality in the canton of Zürich in northern Switzerland, known as a suburban residential and industrial area near the city of Zürich.
-
E.
Richterswil
Richterswil is a picturesque municipality on the shores of Lake Zurich in the canton of Zurich, Switzerland.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4fc13408190b06868df03c5c29b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f954e44481909098a0b23a687d5e |
completed | April 21, 2026, 4:13 a.m. |
Created at: April 16, 2026, 12:50 p.m.