Triple
T35272666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Way 2 Sexy |
E1018710
|
entity |
| Predicate | hasChorusSampleFrom |
P45511
|
FINISHED |
| Object | I'm Too Sexy |
—
|
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: I'm Too Sexy | Statement: [Way 2 Sexy, hasChorusSampleFrom, I'm Too Sexy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChorusSampleFrom Context triple: [Way 2 Sexy, hasChorusSampleFrom, I'm Too Sexy]
-
A.
hasChorusSample
chosen
Indicates that one musical work incorporates a sampled portion of the chorus from another work.
-
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.
hasChorusIn
Indicates that a musical work includes a chorus section within the specified part or segment.
-
D.
hasChorus
Indicates that something (typically a song or musical piece) includes a chorus section as part of its structure.
-
E.
hasChorusHook
Indicates that a musical work features a prominent, recurring chorus section that serves as a memorable hook.
- 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_69f76de5c4788190896ad598ae7d6bc6 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fecd0a732c819097bdd3eb69b6158c |
completed | May 9, 2026, 5:58 a.m. |
| PD | Predicate disambiguation | batch_69fecc0318d481908b5b20598a76a9fe |
completed | May 9, 2026, 5:54 a.m. |
Created at: May 3, 2026, 4:02 p.m.