Triple
T32242275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Different for Girls |
E823647
|
entity |
| Predicate | hasTransgenderProtagonist |
P38674
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Different for Girls, hasTransgenderProtagonist, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTransgenderProtagonist Context triple: [Different for Girls, hasTransgenderProtagonist, true]
-
A.
hasCrossDressingProtagonist
Indicates that the main character in the work regularly dresses in clothing traditionally associated with another gender.
-
B.
protagonistGenderIdentity
chosen
Indicates the gender identity attributed to or expressed by the protagonist in a given context.
-
C.
protagonistGenderIdentityTheme
Indicates that the work explores themes related to the protagonist’s gender identity and its development, expression, or impact within the narrative.
-
D.
protagonistGenderSelectable
Indicates that the gender of the story’s main character can be chosen or customized by the player or user.
-
E.
protagonistBiologicalSex
Indicates the biological sex assigned to the protagonist in the context of the described scenario or work.
- 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_69f3490cdda88190a9d61e11252a771f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69feff70fbec8190b1ff5f943f29613e |
completed | May 9, 2026, 9:33 a.m. |
| PD | Predicate disambiguation | batch_69fefbcd5b7881909cfe52b32f8a4301 |
completed | May 9, 2026, 9:18 a.m. |
Created at: May 1, 2026, 12:40 a.m.