Triple
T1915567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iris Steensma |
E40008
|
entity |
| Predicate | notableThemeAssociation |
P7671
|
FINISHED |
| Object | child prostitution in cinema |
—
|
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: child prostitution in cinema | Statement: [Iris Steensma, notableThemeAssociation, child prostitution in cinema]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableThemeAssociation Context triple: [Iris Steensma, notableThemeAssociation, child prostitution in cinema]
-
A.
notableTheme
chosen
Indicates that a particular theme is prominently featured in, or strongly associated with, an entity such as a work, event, or body of content.
-
B.
notablyAssociatedWith
Indicates that one entity is prominently or distinctively connected with another in a way that is especially noteworthy or remarkable.
-
C.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
-
D.
notableCategory
Indicates that an entity is recognized as notable or significant within a particular category or classification.
-
E.
notableWorkSubject
Indicates that a work is notably associated with a particular subject, such as a person, topic, or entity, as its primary focus or theme.
- 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_69a8864298748190a2f2fd34f7ef8d77 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb1e517e8819086e4bf5a305aeb25 |
completed | March 7, 2026, 5:04 a.m. |
| PD | Predicate disambiguation | batch_69abafed2ab481908920334e77b1021b |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.