Triple
T1917405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Menaggio |
E40048
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Lugano |
E178117
|
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: Lugano | Statement: [Menaggio, locatedNear, Lugano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lugano Context triple: [Menaggio, locatedNear, Lugano]
-
A.
Lugano
chosen
Lugano is a picturesque Swiss city in the Italian-speaking canton of Ticino, known for its lakeside setting on Lake Lugano, surrounding mountains, and role as a regional financial and cultural center.
-
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.
Montreux
Montreux is a picturesque resort town in southwestern Switzerland, renowned for its lakeside promenade, mild microclimate, and the annual Montreux Jazz Festival.
-
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.
Lausanne
Lausanne is a major Swiss city on the shores of Lake Geneva, known for hosting the International Olympic Committee and its vibrant cultural and academic institutions.
- 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_69a8864298748190a2f2fd34f7ef8d77 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb2107fe48190bafff825f1f805ad |
completed | March 7, 2026, 5:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae95e5cf008190a6638bb2c8d4d505 |
completed | March 9, 2026, 9:41 a.m. |
Created at: March 4, 2026, 7:35 p.m.