Triple
T10509411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Iseo |
E247871
|
entity |
| Predicate | hasShoreSettlement |
P16159
|
FINISHED |
| Object |
Pisogne
Pisogne is a picturesque town in northern Italy’s Lombardy region, known as a lakeside resort and historic gateway to the Val Camonica area.
|
E872745
|
NE FINISHED |
How this triple was built (4 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: Pisogne | Statement: [Lake Iseo, hasShoreSettlement, Pisogne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pisogne Context triple: [Lake Iseo, hasShoreSettlement, Pisogne]
-
A.
Desio
Desio is an Italian surname most notably associated with Ardito Desio, a prominent geologist and mountaineer involved in the first successful ascent of K2.
-
B.
Pescia
Pescia is a historic Tuscan town in central Italy known for its paper production, floriculture, and medieval architecture.
-
C.
Gargnano
Gargnano is a small town on the western shore of Lake Garda in northern Italy, known for its scenic lakeside setting and historic villas.
-
D.
Cesenatico
Cesenatico is a historic Adriatic seaside town in Italy, renowned for its canal harbor designed by Leonardo da Vinci and its popular beach tourism.
-
E.
Peschiera Borromeo
Peschiera Borromeo is a municipality in the Metropolitan City of Milan in northern Italy, situated in the Lombardy region.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Pisogne Triple: [Lake Iseo, hasShoreSettlement, Pisogne]
Generated description
Pisogne is a picturesque town in northern Italy’s Lombardy region, known as a lakeside resort and historic gateway to the Val Camonica area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pisogne Target entity description: Pisogne is a picturesque town in northern Italy’s Lombardy region, known as a lakeside resort and historic gateway to the Val Camonica area.
-
A.
Desio
Desio is an Italian surname most notably associated with Ardito Desio, a prominent geologist and mountaineer involved in the first successful ascent of K2.
-
B.
Pescia
Pescia is a historic Tuscan town in central Italy known for its paper production, floriculture, and medieval architecture.
-
C.
Gargnano
Gargnano is a small town on the western shore of Lake Garda in northern Italy, known for its scenic lakeside setting and historic villas.
-
D.
Cesenatico
Cesenatico is a historic Adriatic seaside town in Italy, renowned for its canal harbor designed by Leonardo da Vinci and its popular beach tourism.
-
E.
Peschiera Borromeo
Peschiera Borromeo is a municipality in the Metropolitan City of Milan in northern Italy, situated in the Lombardy region.
- F. None of above. chosen
Provenance (5 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509b359ac8190b3683cc6b9c70a71 |
completed | April 7, 2026, 1:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d94b13f4fc8190863d6e1aa7da5733 |
completed | April 10, 2026, 7:10 p.m. |
| NEDg | Description generation | batch_69d94c6fa9ac8190819a399754d2bd15 |
completed | April 10, 2026, 7:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d953440a508190a50d1897cdbeba03 |
completed | April 10, 2026, 7:45 p.m. |
Created at: April 6, 2026, 12:27 p.m.