Triple
T10035024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valtellina |
E204943
|
entity |
| Predicate | hasSubregion |
P285
|
FINISHED |
| Object |
Grumello
Grumello is a renowned subregion of Italy’s Valtellina wine area, noted especially for its high-quality Nebbiolo-based red wines.
|
E845194
|
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: Grumello | Statement: [Valtellina, hasSubregion, Grumello]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grumello Context triple: [Valtellina, hasSubregion, Grumello]
-
A.
Montebelluna
Montebelluna is a town in the Veneto region of northern Italy, known for its footwear industry and proximity to the foothills of the Dolomite mountains.
-
B.
Chiampo
Chiampo is a town and comune in the Veneto region of northern Italy, known historically for its marble and leather industries.
-
C.
Loiano
Loiano is a small Italian town in the Emilia-Romagna region, known for its Apennine hillside setting and astronomical observatory.
-
D.
Marsciano
Marsciano is a town and comune in the Umbria region of central Italy, known for its medieval historic center and agricultural surroundings.
-
E.
Monteveglio
Monteveglio is a small historic town in the Emilia-Romagna region of northern Italy, known for its medieval architecture and surrounding hilly countryside.
- 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: Grumello Triple: [Valtellina, hasSubregion, Grumello]
Generated description
Grumello is a renowned subregion of Italy’s Valtellina wine area, noted especially for its high-quality Nebbiolo-based red wines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Grumello Target entity description: Grumello is a renowned subregion of Italy’s Valtellina wine area, noted especially for its high-quality Nebbiolo-based red wines.
-
A.
Montebelluna
Montebelluna is a town in the Veneto region of northern Italy, known for its footwear industry and proximity to the foothills of the Dolomite mountains.
-
B.
Chiampo
Chiampo is a town and comune in the Veneto region of northern Italy, known historically for its marble and leather industries.
-
C.
Loiano
Loiano is a small Italian town in the Emilia-Romagna region, known for its Apennine hillside setting and astronomical observatory.
-
D.
Marsciano
Marsciano is a town and comune in the Umbria region of central Italy, known for its medieval historic center and agricultural surroundings.
-
E.
Monteveglio
Monteveglio is a small historic town in the Emilia-Romagna region of northern Italy, known for its medieval architecture and surrounding hilly countryside.
- 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_69ca834d77188190ad645e33e8ca3200 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdce4a515c8190baec86d924623b12 |
completed | April 2, 2026, 2:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d3003098c0819093da30f98438680f |
completed | April 6, 2026, 12:37 a.m. |
| NEDg | Description generation | batch_69d301dd614481909b357f319ba5e876 |
completed | April 6, 2026, 12:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d302978e808190a9f5371a2bf4abce |
completed | April 6, 2026, 12:47 a.m. |
Created at: March 30, 2026, 8:55 p.m.