Triple
T11912713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Fernando |
E283433
|
entity |
| Predicate | associatedWithCharacter |
P1481
|
FINISHED |
| Object | Rocco |
E281075
|
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: Rocco | Statement: [Don Fernando, associatedWithCharacter, Rocco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rocco Context triple: [Don Fernando, associatedWithCharacter, Rocco]
-
A.
Rocco
chosen
Rocco is a central character in Beethoven’s opera "Fidelio," serving as the prison jailer whose actions and moral choices significantly influence the drama’s unfolding.
-
B.
Rocco
Rocco is a supporting character in *The Boondock Saints* who becomes an ally and accomplice to the vigilante brothers Murphy and Connor MacManus.
-
C.
Rocco
Rocco is a masculine given name of Italian origin commonly used in various European and American cultures.
-
D.
Rocco
Rocco is a Brazilian publishing house known for releasing major international bestsellers, including works like Paulo Coelho’s "The Alchemist."
-
E.
Roberto
Roberto is a masculine given name commonly used in Romance-language countries, equivalent to the English name Robert.
- 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_69d6ab2c07e88190ba13b0d21fd6cf33 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8e528f6748190ac873a040a61fa93 |
completed | April 10, 2026, 11:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4185fd3588190807cc2906c4ce3fd |
completed | May 1, 2026, 3:05 a.m. |
Created at: April 8, 2026, 9:44 p.m.