Triple
T22710431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Province of Bologna |
E561576
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Imola |
—
|
NE NERFINISHED |
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: Imola | Statement: [Province of Bologna, contains, Imola]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Imola Context triple: [Province of Bologna, contains, Imola]
-
A.
Imola
chosen
Imola is a historic city in Italy’s Emilia-Romagna region, best known for its Formula One racing circuit, the Autodromo Enzo e Dino Ferrari.
-
B.
Monza
Monza is a historic city in northern Italy renowned for its royal villa and the Autodromo Nazionale Monza Formula One racing circuit.
-
C.
Ostana
Ostana is a small alpine village in Italy’s Piedmont region known for its efforts to preserve Occitan language and culture.
-
D.
Cesena
Cesena is a historic city in the Emilia-Romagna region of northern Italy, known for its medieval center and the UNESCO-listed Malatestiana Library.
-
E.
Pesaro
Pesaro is a coastal city on Italy’s Adriatic Sea, known for its Renaissance architecture, seaside resorts, and as the birthplace of composer Gioachino Rossini.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454f1348819088d83f420925a5c1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17907d7288190bb53f76974f95cef |
completed | April 29, 2026, 3:20 a.m. |
Created at: April 17, 2026, 3:17 p.m.