Triple
T21590302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hit & Miss |
E532759
|
entity |
| Predicate | mainCharacterGenderIdentity |
P38674
|
FINISHED |
| Object | transgender woman |
—
|
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: transgender woman | Statement: [Hit & Miss, mainCharacterGenderIdentity, transgender woman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCharacterGenderIdentity Context triple: [Hit & Miss, mainCharacterGenderIdentity, transgender woman]
-
A.
protagonistGenderIdentity
chosen
Indicates the gender identity attributed to or expressed by the protagonist in a given context.
-
B.
genderOfPersona
Indicates the gender identity associated with a given persona.
-
C.
hasGenderIdentity
Indicates that an entity identifies with or experiences a particular gender.
-
D.
genderCustom
Indicates that an entity has a user-specified or non-standard gender designation beyond predefined gender categories.
-
E.
protagonistGenderSelectable
Indicates that the gender of the story’s main character can be chosen or customized by the player or user.
- 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_69e0c46251648190876f0427cf2d321b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eefadd0ec88190929c76137bd1603e |
completed | April 27, 2026, 5:57 a.m. |
| PD | Predicate disambiguation | batch_69e632109d048190b4ac3f14fe48d1a0 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:32 p.m.