Triple
T6428416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antonio Pigafetta |
E128116
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Vicenza |
E63542
|
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: Vicenza | Statement: [Antonio Pigafetta, birthPlace, Vicenza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vicenza Context triple: [Antonio Pigafetta, birthPlace, Vicenza]
-
A.
Vicenza
chosen
Vicenza is a historic city in northeastern Italy renowned for its Palladian architecture and cultural heritage.
-
B.
Treviso
Treviso is a historic city in northeastern Italy’s Veneto region, known for its medieval walls, canals, and proximity to Venice.
-
C.
Padua
Padua is a historic city in northern Italy renowned as a major cultural and academic center, home to one of Europe’s oldest universities.
-
D.
Verona
Verona is a historic city in northern Italy renowned for its well-preserved Roman architecture and its association with Shakespeare’s "Romeo and Juliet."
-
E.
Verona
Verona is a small borough in Allegheny County, Pennsylvania, situated along the Allegheny River just northeast of Pittsburgh.
- 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_69c00838de888190af2eec0b80495efa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c06922a27881908c5571f2aa31e0c1 |
completed | March 22, 2026, 10:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6eec623c081908352580b64218ec4 |
completed | March 27, 2026, 8:55 p.m. |
Created at: March 22, 2026, 4:44 p.m.