Triple
T20339475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ecstasy (1933 film) |
E495700
|
entity |
| Predicate | featuresOnscreenFemaleNudity |
P101247
|
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: [Ecstasy (1933 film), featuresOnscreenFemaleNudity, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresOnscreenFemaleNudity Context triple: [Ecstasy (1933 film), featuresOnscreenFemaleNudity, true]
-
A.
nudity
chosen
Indicates that an entity is unclothed or exposes parts of the body typically covered, representing a state or depiction of being nude.
-
B.
depictsSex
Indicates that one entity visually represents or portrays sexual activity or sexual content involving another entity.
-
C.
portraysFemaleSexualityPositively
Indicates that the subject represents or depicts female sexuality in an affirming, respectful, and positive manner.
-
D.
viewOnWomen
Indicates a person's attitudes, beliefs, or perspectives regarding women and gender roles.
-
E.
hasSexualityCharacteristic
Indicates that an entity possesses a specific sexual orientation or sexuality-related characteristic.
- 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_69e0b4a1a09881908d97270d6971a25a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678342a0081908ede8006eb5506a3 |
completed | April 20, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_69e57636b4808190bc2855af48a3ccdc |
completed | April 20, 2026, 12:41 a.m. |
Created at: April 16, 2026, 11:23 a.m.