Triple
T1040211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Piedmontese |
E22452
|
entity |
| Predicate | closelyRelatedTo |
P37
|
FINISHED |
| Object | Lombard |
E75301
|
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: Lombard | Statement: [Piedmontese, closelyRelatedTo, Lombard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lombard Context triple: [Piedmontese, closelyRelatedTo, Lombard]
-
A.
Lombard
chosen
Lombard is a Gallo-Italic Romance language traditionally spoken in and around Milan and across much of Lombardy in northern Italy.
-
B.
Pavia
Pavia is a historic city in northern Italy, known for its ancient university, medieval architecture, and significant role in Lombardy’s cultural and academic life.
-
C.
Certaldo
Certaldo is a historic Tuscan town in central Italy, best known as the birthplace and longtime home of the writer Giovanni Boccaccio.
-
D.
Milanollo
Milanollo is a well-known British military march associated with the Coldstream Guards regiment.
-
E.
Lucca
Lucca is a historic Tuscan city renowned for its well-preserved Renaissance walls, medieval architecture, and charming old town.
- 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_69a493d91478819094cc01fb65564bc1 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b82e4d2c81909ca1264852baf04d |
completed | March 1, 2026, 10:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3bc58d8c8190b9dc7a4bc986abcb |
completed | March 7, 2026, 2:52 p.m. |
Created at: March 1, 2026, 7:41 p.m.