Triple
T18634310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | She Used to Wanna Be a Ballerina |
E455502
|
entity |
| Predicate | featuresRockArrangements |
P89596
|
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: [She Used to Wanna Be a Ballerina, featuresRockArrangements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresRockArrangements Context triple: [She Used to Wanna Be a Ballerina, featuresRockArrangements, true]
-
A.
hasMusicalArrangementCharacteristic
chosen
Indicates that a musical arrangement possesses a specific characteristic, feature, or quality.
-
B.
hasPianoArrangement
Indicates that one entity has a version or adaptation of it arranged specifically for piano.
-
C.
famousArrangement
Indicates that an arrangement or configuration is widely recognized or celebrated.
-
D.
orchestralArrangement
Indicates that one musical work is arranged or adapted specifically for performance by an orchestra.
-
E.
notableArrangementOf
Indicates that one entity is a significant or noteworthy configuration, ordering, or spatial organization of the other entity.
- 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_69d8d38cc7948190a55ea64e5638994e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54fc74d208190bfda63b5b0b160cd |
completed | April 19, 2026, 9:57 p.m. |
| PD | Predicate disambiguation | batch_69e478d4a7948190a4bb9223bb5dddfc |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:46 a.m.