Triple
T30917254
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Riptide |
E787613
|
entity |
| Predicate | leadCharacterGenderFocus |
P21355
|
FINISHED |
| Object | female protagonist |
—
|
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 protagonist | Statement: [Riptide, leadCharacterGenderFocus, female protagonist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterGenderFocus Context triple: [Riptide, leadCharacterGenderFocus, female protagonist]
-
A.
hasLeadCharacterGender
chosen
Indicates that the primary or lead character in a work has a specified gender.
-
B.
leadCharacterBasedOn
Indicates that a lead character is derived from, inspired by, or adapted from a particular source entity (such as a real person, another character, or existing work).
-
C.
characterInFocus
Indicates that a particular character is the primary subject or focal point within a given context, scene, or narrative segment.
-
D.
hasGenderFocus
Indicates that something is specifically concerned with, oriented toward, or primarily addressing a particular gender or gender-related issues.
-
E.
femaleRole
Indicates that the role, function, or position involved is associated with or designated as female.
- 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_69f224bfaca88190b9d0dfcc86297fe9 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ed5d008190831cf8e44cce28af |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 29, 2026, 8:51 p.m.