Triple
T11475647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Giovanni |
E272018
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Don Giovanni |
E272018
|
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: Don Giovanni | Statement: [Don Giovanni, character, Don Giovanni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don Giovanni Context triple: [Don Giovanni, character, Don Giovanni]
-
A.
Don Giovanni
chosen
Don Giovanni is a renowned opera by Wolfgang Amadeus Mozart that blends dark comedy and drama in the tale of the libertine nobleman Don Juan.
-
B.
Farindola
Farindola is a small Italian hill town in the Abruzzo region, known for its traditional pecorino cheese and scenic location on the slopes of the Gran Sasso massif.
-
C.
L'Orfeo
L'Orfeo is a pioneering early Baroque opera by Claudio Monteverdi, often regarded as one of the first great masterpieces of the operatic repertoire.
-
D.
Rigoletto
Rigoletto is a renowned opera by Giuseppe Verdi, celebrated for its dramatic intensity and iconic arias such as "La donna è mobile."
-
E.
Capriccio
Capriccio is a late opera by Richard Strauss that explores the primacy of words versus music in opera through an elegant, conversational “conversation piece” set in 18th-century France.
- 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_69d6aae0c8d881908a5a360c0be3242e |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8294c8dc48190a515f83c99405a3b |
completed | April 9, 2026, 10:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5e965eebc8190822247b1abc13483 |
completed | April 20, 2026, 8:52 a.m. |
Created at: April 8, 2026, 9:36 p.m.