Triple
T27808109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madea |
E702445
|
entity |
| Predicate | fictionalGenderPresentation |
P92864
|
FINISHED |
| Object | female |
—
|
LITERAL 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: female | Statement: [Madea, fictionalGenderPresentation, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalGenderPresentation Context triple: [Madea, fictionalGenderPresentation, female]
-
A.
fictionalGender
chosen
Indicates that one entity has a gender identity or classification that exists only within a fictional or imaginary context.
-
B.
protagonistGenderIdentity
Indicates the gender identity attributed to or expressed by the protagonist in a given context.
-
C.
genderOfPersona
Indicates the gender identity associated with a given persona.
-
D.
genderVariant
Indicates that an entity’s gender identity or expression differs from traditional or expected norms associated with their assigned sex or gender.
-
E.
genderConfiguration
Indicates how the genders of the involved entities are arranged or combined within a particular relationship or context.
- 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_69ef840a16748190926719ab96120bae |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
Created at: April 27, 2026, 5:40 p.m.