Triple
T8428668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TQG |
E199063
|
entity |
| Predicate | hasChorusFeature |
P79253
|
FINISHED |
| Object | catchy hook |
—
|
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: catchy hook | Statement: [TQG, hasChorusFeature, catchy hook]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChorusFeature Context triple: [TQG, hasChorusFeature, catchy hook]
-
A.
hasChorus
Indicates that something (typically a song or musical piece) includes a chorus section as part of its structure.
-
B.
hasChorusBy
Indicates that something (typically a musical work or song) includes a chorus section that is performed, written, or provided by a specified entity.
-
C.
hasChorusStyle
Indicates that an entity is associated with a particular style or manner in which a chorus is performed or structured.
-
D.
hasChorusHook
chosen
Indicates that a musical work features a prominent, recurring chorus section that serves as a memorable hook.
-
E.
hasChorusSample
Indicates that one musical work incorporates a sampled portion of the chorus from another work.
- 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_69ca8313c99081909a5c6d83b91de5b3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe30fba4081908bfdef3faf5baceb |
completed | March 31, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69cbd0ec200c8190b0299e2b0b4bdcc2 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:07 p.m.