Triple
T22092505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grease Live |
E545944
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Carly Rae Jepsen |
—
|
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: Carly Rae Jepsen | Statement: [Grease Live, stars, Carly Rae Jepsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carly Rae Jepsen Context triple: [Grease Live, stars, Carly Rae Jepsen]
-
A.
Carly Rae Jepsen
chosen
Carly Rae Jepsen is a Canadian pop singer and songwriter best known for her global hit single "Call Me Maybe" and her critically acclaimed album "Emotion."
-
B.
Anna Jepsen
Anna Jepsen is a person notable enough to be recognized as a prominent bearer of the surname Jepsen.
-
C.
Juno Skinner
Juno Skinner is a seductive and ruthless art dealer who secretly collaborates with terrorists in the action film "True Lies."
-
D.
Colbie Caillat
Colbie Caillat is an American pop and folk-pop singer-songwriter known for mellow, acoustic hits like "Bubbly" and "Realize."
-
E.
Alessia Cara
Alessia Cara is a Canadian singer-songwriter known for her soulful pop music and breakout hits like "Here" and "Scars to Your Beautiful."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e6b1d881909bf0f4a52199354c |
completed | April 28, 2026, 9:38 p.m. |
Created at: April 16, 2026, 8:29 p.m.