Triple
T8874790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camillo De Lellis |
E211246
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Camillo De Lellis |
E211246
|
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: Camillo De Lellis | Statement: [Camillo De Lellis, name, Camillo De Lellis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Camillo De Lellis Context triple: [Camillo De Lellis, name, Camillo De Lellis]
-
A.
Camillo De Lellis
chosen
Camillo De Lellis is an Italian mathematician renowned for his contributions to geometric measure theory and the calculus of variations.
-
B.
Lorenzo Senatore
Lorenzo Senatore is a cinematographer known for his work on feature films such as the military drama "Megan Leavey."
-
C.
Saverio Raimondo
Saverio Raimondo is an Italian stand-up comedian, actor, and television personality known for his sharp, satirical humor.
-
D.
Joseph Oriolo
Joseph Oriolo was an American cartoonist, animator, and producer best known for co-creating the character Casper the Friendly Ghost and for his work on various animated television series.
-
E.
Peter Gennaro
Peter Gennaro was an American choreographer and dancer renowned for his work on Broadway musicals and television, particularly during the mid-20th century.
- 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_69ca838e78748190934d82db3104f855 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc614451d081908804430a72d00edf |
completed | April 1, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd082bbe88190a207d39f9295735e |
completed | April 3, 2026, 2:36 p.m. |
Created at: March 30, 2026, 6:52 p.m.