Triple
T910975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lombardy |
E19656
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Lecco |
E35247
|
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: Lecco | Statement: [Lombardy, hasMajorCity, Lecco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lecco Context triple: [Lombardy, hasMajorCity, Lecco]
-
A.
Lecco
chosen
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.
-
B.
Varese
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.
-
C.
Bergamo
Bergamo is a historic city in northern Italy known for its medieval walled upper town, rich artistic heritage, and strategic location at the foothills of the Alps.
-
D.
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.
-
E.
Varenna
Varenna is a picturesque historic village in northern Italy known for its colorful lakeside houses, romantic promenades, and scenic views over Lake Como.
- 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2de5b008190851852331db41324 |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae02eda1048190b5452b849315863f |
completed | March 8, 2026, 11:14 p.m. |
Created at: March 1, 2026, 7:39 p.m.