Triple
T3249781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Storm |
E68147
|
entity |
| Predicate | portraysFemaleSexualityPositively |
P46829
|
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: [The Storm, portraysFemaleSexualityPositively, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysFemaleSexualityPositively Context triple: [The Storm, portraysFemaleSexualityPositively, true]
-
A.
depictsSex
Indicates that one entity visually represents or portrays sexual activity or sexual content involving another entity.
-
B.
coneSex
Indicates a sexual or mating relationship involving a cone-shaped structure or entity.
-
C.
viewsSexualityAs
Indicates how one entity conceptually interprets, judges, or understands the sexuality of another entity.
-
D.
hasStrongFemaleCharacters
Indicates that the work features prominent, well-developed female characters who display agency, complexity, and significant influence on the narrative or outcome.
-
E.
viewOnPleasure
Indicates a subject’s stance, opinion, or attitude toward the concept or experience of pleasure.
- F. None of above. chosen
Provenance (4 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_69ad858e4c708190aa31d486cfee8a6a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaf3fc3c8819080ac95974581ca0e |
completed | March 8, 2026, 5:17 p.m. |
| PD | Predicate disambiguation | batch_69ada41837e48190933572165be0ca38 |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada525bb2c8190b773efe6d696b6ab |
completed | March 8, 2026, 4:34 p.m. |
Created at: March 8, 2026, 3:09 p.m.