Triple
T14849734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pietro Verri |
E349194
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Il Caffè |
E349198
|
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: Il Caffè | Statement: [Pietro Verri, notableWork, Il Caffè]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Il Caffè Context triple: [Pietro Verri, notableWork, Il Caffè]
-
A.
Il Caffè
chosen
Il Caffè was an influential 18th-century Italian Enlightenment periodical that served as a key forum for the reformist ideas of the Milanese intellectual circle Accademia dei Pugni.
-
B.
La bottega del caffè
La bottega del caffè is a classic 18th-century Italian comedy by Carlo Goldoni that portrays the intertwined lives and intrigues of patrons in a Venetian coffeehouse.
-
C.
Le Café
Le Café is a satirical verse dialogue by French poet Jean-Baptiste Rousseau that critiques contemporary society and literary culture through a conversation set in a coffeehouse.
-
D.
Sultana del Café
Sultana del Café is a nickname for Jipijapa, a town in Ecuador renowned for its coffee production and traditional culture.
-
E.
The Cafe
The Cafe is a casual dining spot where people can relax, socialize, and enjoy beverages and light meals.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded43eee188190bf24dc475b3abe28 |
completed | April 14, 2026, 11:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6504ac6081908074231cf628fd39 |
completed | May 8, 2026, 10:34 p.m. |
Created at: April 10, 2026, 1:54 a.m.