Triple
T11475633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Giovanni |
E272018
|
entity |
| Predicate | genre |
P14
|
FINISHED |
| Object | opera seria |
E600006
|
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: opera seria | Statement: [Don Giovanni, genre, opera seria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: opera seria Context triple: [Don Giovanni, genre, opera seria]
-
A.
opera seria
chosen
Opera seria is an 18th-century Italian operatic genre characterized by serious, often classical or mythological subjects, virtuosic vocal writing, and a formal structure centered on da capo arias.
-
B.
Ópera
Ópera is a central Madrid Metro station located near the historic Teatro Real opera house and Plaza de Oriente.
-
C.
Italian opera
Italian opera is a long-standing tradition of sung drama from Italy, renowned for its expressive melodies, virtuosic vocal writing, and influential composers such as Verdi, Puccini, and Rossini.
-
D.
OPERA
OPERA was a long-baseline neutrino oscillation experiment at the Gran Sasso National Laboratory in Italy, designed to detect tau neutrinos in a beam sent from CERN.
-
E.
Opéra
Opéra is a major Paris Métro station and transport hub located near the Palais Garnier in central Paris.
- 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.