Triple
T7900348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Story Sunlight |
E183434
|
entity |
| Predicate | hasPortrayedSex |
P15023
|
FINISHED |
| Object | female figures |
—
|
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 figures | Statement: [Second Story Sunlight, hasPortrayedSex, female figures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPortrayedSex Context triple: [Second Story Sunlight, hasPortrayedSex, female figures]
-
A.
hasSex
Indicates that one entity engages in sexual activity with another entity.
-
B.
depictsSex
chosen
Indicates that one entity visually represents or portrays sexual activity or sexual content involving another entity.
-
C.
leadActorSexualOrientation
Indicates the sexual orientation of the lead actor in a work or production.
-
D.
wasPortrayedAs
Indicates that one entity has been depicted or represented in the form or role of another entity, typically within some medium or context.
-
E.
portraysFemaleSexualityPositively
Indicates that the subject represents or depicts female sexuality in an affirming, respectful, and positive manner.
- 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_69ca828d13088190b222be7aa9f9315c |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a3dc2208190a6fea93b60b8daca |
completed | March 31, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69cae92d94448190b4425bbfb64c658c |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:02 p.m.