Triple
T23090189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Translations of The Threepenny Opera |
E575723
|
entity |
| Predicate | hasNotableCharacter |
P7927
|
FINISHED |
| Object | Jenny |
—
|
NE NERFINISHED |
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: Jenny | Statement: [Translations of The Threepenny Opera, hasNotableCharacter, Jenny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jenny Context triple: [Translations of The Threepenny Opera, hasNotableCharacter, Jenny]
-
A.
Jenny
Jenny is a caring and protective regal blue tang fish who is Dory’s mother in the animated film "Finding Dory."
-
B.
Jenny
chosen
Jenny is a central character in Kurt Weill and Bertolt Brecht’s opera "Rise and Fall of the City of Mahagonny," often portrayed as a pragmatic, disillusioned prostitute who embodies the work’s critique of capitalist excess and moral decay.
-
C.
Jenny
Jenny is the main character of the story "Mosquitoes," around whom the narrative and its central events revolve.
-
D.
Jenny
Jenny is the wife of Charlie.
-
E.
Jenny
Jenny is a Welsh Labour politician and Member of the Senedd known for her work on social justice and community issues in Cardiff.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245bf3e3c819086d3448720efc01b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18da99bec81908ecadf8dab10d1b7 |
completed | April 29, 2026, 4:48 a.m. |
Created at: April 17, 2026, 3:57 p.m.