Triple
T2915591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olona |
E78597
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Varese |
E214629
|
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: Varese | Statement: [Olona, nearbyCity, Varese]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Varese Context triple: [Olona, nearbyCity, Varese]
-
A.
Varese
chosen
Varese is a city in northern Italy known for its lakeside setting, surrounding Prealps, and role as an important economic and cultural center in the Lombardy region.
-
B.
Lecco
Lecco is an Italian town in the Lombardy region, known for its scenic location at the southeastern tip of Lake Como and its surrounding Alpine foothills.
-
C.
Busto Arsizio
Busto Arsizio is an industrial city in the Lombardy region of northern Italy, known for its textile and manufacturing heritage and its location within the greater Milan metropolitan area.
-
D.
Legnano
Legnano is a town in the Lombardy region of northern Italy, historically known for its medieval Battle of Legnano and its industrial development.
-
E.
Brescia
Brescia is a historic industrial and cultural city in northern Italy, known for its Roman and medieval architecture and its role as an economic hub.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad96a1a9f8819095fe3198e9d3f6b0 |
completed | March 8, 2026, 3:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b224a78bbc8190b4f4cdb058d5a176 |
completed | March 12, 2026, 2:27 a.m. |
Created at: March 8, 2026, 2:52 p.m.