Triple
T22468926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A6 motorway |
E555436
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Thun |
—
|
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: Thun | Statement: [A6 motorway, connects, Thun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thun Context triple: [A6 motorway, connects, Thun]
-
A.
Thun
chosen
Thun is a historic Swiss town in the canton of Bern, known for its medieval old town, lakeside setting on Lake Thun, and views of the surrounding Alps.
-
B.
Brienz
Brienz is a picturesque Swiss village in the Bernese Oberland, known for its lakeside setting on Lake Brienz and its traditional woodcarving craftsmanship.
-
C.
Entlebuch
Entlebuch is a municipality in the canton of Lucerne in central Switzerland, known for its rural landscape and inclusion in the UNESCO Entlebuch Biosphere Reserve.
-
D.
Sihlwald
Sihlwald is a large forest and nature reserve near Zurich, Switzerland, known for its protected, near-natural woodland and recreational hiking trails.
-
E.
Saanen
Saanen is a picturesque Swiss village in the Bernese Oberland known for its traditional chalets, alpine scenery, and proximity to the upscale resort town of Gstaad.
- 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_69e11e52c2048190952dc5df209b9bed |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15bdda62c8190937ac13a4481b4b7 |
completed | April 29, 2026, 1:16 a.m. |
Created at: April 16, 2026, 8:48 p.m.