Triple
T18504424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Let’s Talk About Sex |
E452162
|
entity |
| Predicate | hasEditedVersions |
P28478
|
FINISHED |
| Object | radio edit with toned-down sexual references |
—
|
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: radio edit with toned-down sexual references | Statement: [Let’s Talk About Sex, hasEditedVersions, radio edit with toned-down sexual references]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEditedVersions Context triple: [Let’s Talk About Sex, hasEditedVersions, radio edit with toned-down sexual references]
-
A.
hasMultipleVersions
chosen
Indicates that an entity exists in more than one distinct version or revision.
-
B.
hasDifferentEditions
Indicates that an entity exists in multiple distinct versions or editions that differ in some characteristics.
-
C.
hasHumanModification
Indicates that an entity has been altered, influenced, or modified as a result of human activity or intervention.
-
D.
has edition or version
Indicates that one entity exists as a particular edition or version of another entity.
-
E.
hasEditionIn
Indicates that one entity has a specific edition or version that exists or is available in another entity (such as a particular format, language, or location).
- 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_69d8d386df84819092355ebb260d848e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53341063c81908361b0eb78794145 |
completed | April 19, 2026, 7:55 p.m. |
| PD | Predicate disambiguation | batch_69e469dbf5208190b6fc49e02a087f54 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:36 a.m.