Triple
T16677268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wayne Swinny |
E405243
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Under Your Skin |
E405249
|
NE 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: Under Your Skin | Statement: [Wayne Swinny, notableWork, Under Your Skin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Under Your Skin Context triple: [Wayne Swinny, notableWork, Under Your Skin]
-
A.
Under Your Skin
chosen
Under Your Skin is a studio album by the American rock band Saliva, known for its hard rock and post-grunge sound.
-
B.
Under My Skin
Under My Skin is the second studio album by Canadian singer-songwriter Avril Lavigne, known for its darker, more mature pop-punk and alternative rock sound.
-
C.
Under My Skin
"Under My Skin" is a rock song by Aerosmith featured on their 2001 album *Just Push Play*.
-
D.
Beneath the Skin
"Beneath the Skin" is the second studio album by Icelandic indie folk/pop band Of Monsters and Men, known for its atmospheric sound and introspective lyrics.
-
E.
In Your Skin
"In Your Skin" is a song featured on the album "Smoke & Mirrors" by the American rock band Imagine Dragons.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d6c805c81909fbe4fcb20eedbe1 |
completed | April 18, 2026, 12:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009194ad188190aae3371c97abc045 |
completed | May 10, 2026, 2:09 p.m. |
Created at: April 10, 2026, 5:19 a.m.