Triple
T6097202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federico Caffè |
E135906
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Caffè |
E366103
|
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: Caffè | Statement: [Federico Caffè, familyName, Caffè]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caffè Context triple: [Federico Caffè, familyName, Caffè]
-
A.
Cappachino
Cappachino is an alias of Cappadonna, an American rapper best known for his longtime affiliation with the Wu-Tang Clan.
-
B.
Caffè Torino
Caffè Torino is a historic and elegant café in Turin, Italy, renowned for its classic Belle Époque atmosphere and role as a traditional meeting place for locals and visitors.
-
C.
Federico Caffè
Federico Caffè was an influential Italian economist and academic known for his work on welfare economics, Keynesian theory, and social justice in economic policy.
-
D.
Caffè Biffi
Caffè Biffi is a historic and elegant Milanese café renowned for its traditional Italian pastries and coffee, located within the iconic Galleria Vittorio Emanuele II.
-
E.
Caffe
chosen
Caffe is an open-source deep learning framework known for its speed and modular design, widely used in computer vision research and applications.
- 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_69c0087cd3c48190b459848c72d84eb1 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05a987ce081908cbe22940f31ee2f |
completed | March 22, 2026, 9:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1358d0e18819084e2acb9e75271b4 |
completed | March 23, 2026, 12:43 p.m. |
Created at: March 22, 2026, 4:12 p.m.