Triple
T16677488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Under Your Skin |
E405249
|
entity |
| Predicate | followedBy |
P78
|
FINISHED |
| Object | In It to Win It |
E405250
|
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: In It to Win It | Statement: [Under Your Skin, followedBy, In It to Win It]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: In It to Win It Context triple: [Under Your Skin, followedBy, In It to Win It]
-
A.
In It to Win It
chosen
"In It to Win It" is a studio album by the American rock band Saliva, showcasing their hard rock and post-grunge sound.
-
B.
Win It All
Win It All is a 2017 American indie dramedy film directed by Joe Swanberg, starring Jake Johnson as a small-time gambler whose life unravels after he mishandles a stash of illicit cash.
-
C.
Power to Win
"Power to Win" is the official club song of the Port Adelaide Football Club in the Australian Football League.
-
D.
Win Some, Lose Some
"Win Some, Lose Some" is a reflective hip-hop track by Big Sean that explores personal struggles, growth, and the costs of success.
-
E.
Tell to Win
"Tell to Win" is a business and leadership book by Hollywood executive Peter Guber that explains how strategic storytelling can be used to persuade, inspire, and drive success.
- 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.