Triple
T28548398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dame Edna: My Gorgeous Life |
E722509
|
entity |
| Predicate | hasFlamboyantProtagonist |
P21469
|
FINISHED |
| Object | Dame Edna Everage |
—
|
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: Dame Edna Everage | Statement: [Dame Edna: My Gorgeous Life, hasFlamboyantProtagonist, Dame Edna Everage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFlamboyantProtagonist Context triple: [Dame Edna: My Gorgeous Life, hasFlamboyantProtagonist, Dame Edna Everage]
-
A.
hasProtagonist
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
-
B.
protagonistIs
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative context.
-
C.
hasHumanProtagonists
Indicates that the primary characters driving the narrative are human beings rather than non-human entities.
-
D.
hasBlackProtagonist
Indicates that the work features a main character whose racial identity is Black.
-
E.
protagonistCharacteristic
chosen
Indicates that a characteristic, trait, or defining quality is attributed to the protagonist in a narrative or scenario.
- F. None of above.
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_69f01a5e42348190b1ffbca26e739c84 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f68805b4848190b75da14996d52a38 |
completed | May 2, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 28, 2026, 3:41 a.m.