Triple
T18334036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenny Matrix |
E439220
|
entity |
| Predicate | givenName |
P17
|
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: [Jenny Matrix, givenName, Jenny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jenny Context triple: [Jenny Matrix, givenName, Jenny]
-
A.
Jenny
Jenny is the main character of the story "Mosquitoes," around whom the narrative and its central events revolve.
-
B.
Jenny
Jenny is a central fictional character in the Australian television drama series "The Newsreader," which follows the turbulent personal and professional lives of broadcast journalists in the 1980s.
-
C.
Jenny
"Jenny" is a French film featuring actress Sylvia Bataille in a significant role.
-
D.
Jenny
Jenny is a caring and protective regal blue tang fish who is Dory’s mother in the animated film "Finding Dory."
-
E.
Jenny
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50ecbc76c8190a80c0c8c8bce1cbd |
completed | April 19, 2026, 5:20 p.m. |
Created at: April 10, 2026, 10:36 a.m.