Triple
T3228789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Owl City |
E67686
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Carly Rae Jepsen |
E322701
|
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: Carly Rae Jepsen | Statement: [Owl City, associatedAct, Carly Rae Jepsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carly Rae Jepsen Context triple: [Owl City, associatedAct, 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.
Colbie Caillat
Colbie Caillat is an American pop and folk-pop singer-songwriter known for mellow, acoustic hits like "Bubbly" and "Realize."
-
D.
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."
-
E.
Mary Lou Jepsen
Mary Lou Jepsen is an American engineer, inventor, and entrepreneur known for her pioneering work in display technology and for co-founding the low-cost computing initiative One Laptop per Child.
- 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_69ad858c61888190a31196310d9b30b5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaeb6f8588190a33a9d6c779e8992 |
completed | March 8, 2026, 5:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b262675b588190bcff98e7fa3a0c77 |
completed | March 12, 2026, 6:51 a.m. |
Created at: March 8, 2026, 3:08 p.m.