Triple
T4490458
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Sempach |
E107358
|
entity |
| Predicate | hasNearbySettlement |
P4647
|
FINISHED |
| Object | Sursee |
E448723
|
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: Sursee | Statement: [Lake Sempach, hasNearbySettlement, Sursee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sursee Context triple: [Lake Sempach, hasNearbySettlement, Sursee]
-
A.
Sursee
chosen
Sursee is a historic Swiss town in the canton of Lucerne, known for its well-preserved medieval old town and scenic setting near Lake Sempach.
-
B.
Selzach
Selzach is a Swiss municipality located in the canton of Solothurn, known for its rural character and proximity to the Jura Mountains.
-
C.
Neuenegg
Neuenegg is a Swiss municipality in the canton of Bern, known for its rural character and location near the city of Bern.
-
D.
Giswil
Giswil is a Swiss municipality in the canton of Obwalden, known for its scenic alpine landscape and location along key routes through central Switzerland.
-
E.
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.
- 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_69bd43f84f788190a1383579c4a595be |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd556e69f88190b9c16afc2afcdbef |
completed | March 20, 2026, 2:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bda41426ec8190a239da38bd3643fd |
completed | March 20, 2026, 7:46 p.m. |
Created at: March 20, 2026, 12:59 p.m.