Triple
T7001753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Lucerne |
E162352
|
entity |
| Predicate | hasTownOnShore |
P969
|
FINISHED |
| Object | Brunnen |
E528286
|
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: Brunnen | Statement: [Lake Lucerne, hasTownOnShore, Brunnen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brunnen Context triple: [Lake Lucerne, hasTownOnShore, Brunnen]
-
A.
Brunnen
chosen
Brunnen is a Swiss lakeside village on Lake Lucerne in the canton of Schwyz, known for its scenic alpine setting and role as a popular tourist destination.
-
B.
Feldbrunnen
Feldbrunnen is a village and municipality in the canton of Solothurn in northwestern Switzerland.
-
C.
Elisenbrunnen
Elisenbrunnen is a historic neoclassical spa pavilion in Aachen, Germany, renowned for its sulfurous thermal springs and role as a symbol of the city’s spa culture.
-
D.
Fraubrunnen
Fraubrunnen is a municipality in the canton of Bern in Switzerland, known for its rural character and location in the Swiss Plateau.
-
E.
Schöner Brunnen
Schöner Brunnen is an ornate 14th-century Gothic fountain in Nuremberg’s main market square, famed for its intricate sculptures and colorful design.
- 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_69c68857ffc08190857dc62cd5253777 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc0f8830819091f4356296234713 |
completed | March 27, 2026, 7:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c76a310eb08190a0fc1de2814aea08 |
completed | March 28, 2026, 5:42 a.m. |
Created at: March 27, 2026, 2:33 p.m.