Triple
T1261605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A1 motorway (Switzerland) |
E12513
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | St. Gallen |
E180328
|
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: St. Gallen | Statement: [A1 motorway (Switzerland), connectsTo, St. Gallen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: St. Gallen Context triple: [A1 motorway (Switzerland), connectsTo, St. Gallen]
-
A.
St. Gallen
chosen
St. Gallen is a historic city in northeastern Switzerland renowned for its UNESCO-listed Abbey of Saint Gall and rich textile heritage.
-
B.
Olten
Olten is a town in the canton of Solothurn in northwestern Switzerland, known as an important railway junction and regional economic center.
-
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.
Zurich
Zurich is the largest city in Switzerland, known as a global financial hub and cultural center situated on the shores of Lake Zurich.
-
E.
Schaffhausen
Schaffhausen is a historic town and capital of the canton of the same name in northern Switzerland, known for its well-preserved medieval old town and proximity to the Rhine Falls.
- 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfc64e648190b9c4f980eb8168aa |
completed | March 1, 2026, 10:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b44eb4706c8190870d99abc140973d |
completed | March 13, 2026, 5:51 p.m. |
Created at: March 1, 2026, 7:50 p.m.