Triple
T14556628
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Mantua |
E341557
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Pegognaga
Pegognaga is a small Italian municipality in the Lombardy region, known for its agricultural landscape and traditional rural character.
|
E1114588
|
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: Pegognaga | Statement: [Province of Mantua, contains, Pegognaga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pegognaga Context triple: [Province of Mantua, contains, Pegognaga]
-
A.
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.
-
B.
Pandino
Pandino is a small Italian town in the Lombardy region, known for its historic Visconti castle and agricultural surroundings.
-
C.
Oggiono
Oggiono is a small town and municipality in the Lombardy region of northern Italy, known for its scenic lakeside setting and proximity to the Alps.
-
D.
Albignasego
Albignasego is a municipality in the Veneto region of northern Italy, situated just south of the city of Padua.
-
E.
Pievepelago
Pievepelago is a small mountain town and comune in the northern Italian region of Emilia-Romagna, known for its Apennine landscapes and outdoor tourism.
- 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: Pegognaga Triple: [Province of Mantua, contains, Pegognaga]
Generated description
Pegognaga is a small Italian municipality in the Lombardy region, known for its agricultural landscape and traditional rural character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pegognaga Target entity description: Pegognaga is a small Italian municipality in the Lombardy region, known for its agricultural landscape and traditional rural character.
-
A.
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.
-
B.
Pandino
Pandino is a small Italian town in the Lombardy region, known for its historic Visconti castle and agricultural surroundings.
-
C.
Oggiono
Oggiono is a small town and municipality in the Lombardy region of northern Italy, known for its scenic lakeside setting and proximity to the Alps.
-
D.
Albignasego
Albignasego is a municipality in the Veneto region of northern Italy, situated just south of the city of Padua.
-
E.
Pievepelago
Pievepelago is a small mountain town and comune in the northern Italian region of Emilia-Romagna, known for its Apennine landscapes and outdoor tourism.
- 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_69d822db9c8481908213ceb39585f792 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb2f1490881908673f429e5288c86 |
completed | April 14, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde16830c0819090a97b073c8e642d |
completed | May 8, 2026, 1:13 p.m. |
| NEDg | Description generation | batch_69fdebe3cb908190a0731bc2b87a7db8 |
completed | May 8, 2026, 1:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fdec35ff7881908e2fece02dc531ef |
completed | May 8, 2026, 1:59 p.m. |
Created at: April 10, 2026, 1:23 a.m.