Triple
T5588018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dame D.O.L.L.A. |
E146802
|
entity |
| Predicate | usesCleanContent |
P64924
|
FINISHED |
| Object | often avoids explicit lyrics |
—
|
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: often avoids explicit lyrics | Statement: [Dame D.O.L.L.A., usesCleanContent, often avoids explicit lyrics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesCleanContent Context triple: [Dame D.O.L.L.A., usesCleanContent, often avoids explicit lyrics]
-
A.
notCleanedFor
Indicates that one entity has not been cleaned, maintained, or cleared in preparation for use by another entity.
-
B.
regulatesContentFor
Indicates that one entity controls, manages, or sets rules governing the content produced, shared, or accessed by another entity.
-
C.
hasUserGeneratedContent
Indicates that the subject contains or is associated with content created directly by users rather than by the system or administrators.
-
D.
GCContent
Indicates the proportion of guanine (G) and cytosine (C) bases relative to the total nucleotide content in a DNA or RNA sequence.
-
E.
hasContentFrom
Indicates that one entity’s content is derived from, includes, or is based on another entity.
- 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_69c009036c408190981a8d690b679b67 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c0209e892c8190b936a05ef2a14d36 |
completed | March 22, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69c01b16b9bc8190ab0b945507d90e05 |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f4032408190a4f0d2eb21ebd870 |
completed | March 22, 2026, 4:56 p.m. |
Created at: March 22, 2026, 3:38 p.m.