Triple
T16682725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porlezza |
E405378
|
entity |
| Predicate | hasBodyOfWater |
P1778
|
FINISHED |
| Object | Lago di Lugano |
E84796
|
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: Lago di Lugano | Statement: [Porlezza, hasBodyOfWater, Lago di Lugano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lago di Lugano Context triple: [Porlezza, hasBodyOfWater, Lago di Lugano]
-
A.
Lake Lugano
chosen
Lake Lugano is a glacial lake in the southern Alps, straddling the border between Switzerland and Italy and known for its picturesque scenery and lakeside towns.
-
B.
Lake Neuchâtel
Lake Neuchâtel is the largest lake entirely within Switzerland, located in the French-speaking western part of the country and known for its scenic shores and surrounding vineyards.
-
C.
Immensee
Immensee is a picturesque lakeside village in the Swiss canton of Schwyz, known for its scenic setting on the shores of Lake Zug.
-
D.
Lake Varese
Lake Varese is a glacial lake in northern Italy known for its scenic surroundings, birdlife, and rowing activities.
-
E.
Lake Sarnen
Lake Sarnen is a scenic alpine lake in the canton of Obwalden in central Switzerland, known for its clear waters and surrounding mountain landscapes.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d70d3f8819087d1bd700c94a83f |
completed | April 18, 2026, 12:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b35ce148190a10322f392cb7366 |
completed | May 10, 2026, 11:56 p.m. |
Created at: April 10, 2026, 5:19 a.m.