Triple
T28962481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BZRP Music Sessions Vol. 53 |
E731941
|
entity |
| Predicate | lyricalTarget |
P134835
|
FINISHED |
| Object | Gerard Piqué |
—
|
NE NERFINISHED |
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: Gerard Piqué | Statement: [BZRP Music Sessions Vol. 53, lyricalTarget, Gerard Piqué]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lyricalTarget Context triple: [BZRP Music Sessions Vol. 53, lyricalTarget, Gerard Piqué]
-
A.
lyricalLanguage
Indicates that something is expressed using poetic, figurative, or highly expressive language.
-
B.
lyricalFunction
Indicates the role or purpose that lyrics serve within a musical or poetic work, such as narrating, expressing emotion, or structuring the piece.
-
C.
lyricalPhrase
Indicates that one entity is a lyrical phrase or line that is part of, derived from, or associated with another entity such as a song, poem, or musical work.
-
D.
lyricalMotive
Indicates a recurring musical or textual idea that serves as a unifying expressive element within a lyrical or vocal work.
-
E.
lyricText
chosen
Indicates that one entity is the lyrical content or words of a song or musical piece associated with another 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_69f043ee242c8190b063248b417c5a69 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c2198208190a3954086c22cfcbf |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 8:50 a.m.