Triple
T22126972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Up All Night |
E546813
|
entity |
| Predicate | followedBy |
P78
|
FINISHED |
| Object | Take Me Home |
—
|
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: Take Me Home | Statement: [Up All Night, followedBy, Take Me Home]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Take Me Home Context triple: [Up All Night, followedBy, Take Me Home]
-
A.
Take Me Home
chosen
"Take Me Home" is a dance-pop song by English singer Sophie Ellis-Bextor that helped establish her solo career in the early 2000s.
-
B.
Take Me Home
"Take Me Home" is a popular 1985 pop song by Phil Collins, noted for its atmospheric production and lyrics inspired in part by the novel "One Flew Over the Cuckoo's Nest."
-
C.
Take Me Home
"Take Me Home" is a song featured on the soundtrack of the James Bond film "For Your Eyes Only."
-
D.
Take Me Home
"Take Me Home" is an independent romantic comedy film written and directed by actor-filmmaker Sam Jaeger, following an impromptu cross-country road trip that sparks an unexpected relationship.
-
E.
Take Me Home
"Take Me Home" is a powerful pop ballad by English singer Jess Glynne, known for its emotional vocals and themes of vulnerability and longing.
- 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_69e11e39bf348190b541bfa16a7b71e0 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12982eaa08190933d3036c020f562 |
completed | April 28, 2026, 9:41 p.m. |
Created at: April 16, 2026, 8:31 p.m.