Triple
T3033961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NPAPI |
E82962
|
entity |
| Predicate | usedBy |
P260
|
FINISHED |
| Object | Opera |
E72095
|
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 | Statement: [NPAPI, usedBy, Opera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Opera Context triple: [NPAPI, usedBy, Opera]
-
A.
Opera
chosen
Opera is a web browser known for its built-in features like a free VPN, ad blocker, and integrated messaging tools.
-
B.
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.
-
C.
World Music Theatre
World Music Theatre is a large outdoor concert amphitheater in Tinley Park, Illinois, known for hosting major touring music acts and festivals.
-
D.
Music for the Theatre
Music for the Theatre is a 1925 jazz-influenced orchestral suite by Aaron Copland that blends modernist harmonies with theatrical, American vernacular styles.
-
E.
opera "Eugene Onegin"
"Eugene Onegin" is a lyric opera in three acts by Pyotr Ilyich Tchaikovsky, based on Alexander Pushkin’s novel in verse and renowned as one of the central works of the Russian operatic repertoire.
- 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_69ad8b21a62881908ec5dd4fba4a187c |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9af13ce48190bda4f5ca0ffe6285 |
completed | March 8, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1dec30d8081909d6ee691e5e51434 |
completed | March 11, 2026, 9:29 p.m. |
Created at: March 8, 2026, 3:01 p.m.