Triple
T13722658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince and The Revolution |
E329075
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object | Take Me with U |
E797796
|
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: Take Me with U | Statement: [Prince and The Revolution, notableSong, Take Me with U]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Take Me with U Context triple: [Prince and The Revolution, notableSong, Take Me with U]
-
A.
Take Me with U
chosen
"Take Me with U" is a pop-rock duet by Prince and Apollonia 6, known for its romantic lyrics and prominent placement on the iconic Purple Rain soundtrack.
-
B.
Take Me
"Take Me" is a 2017 dark comedy film about a struggling entrepreneur who runs a simulated kidnapping service that spirals out of control when he takes on an unusually mysterious client.
-
C.
Take Me to Heart
"Take Me to Heart" is a 1983 pop-rock song by the American band Quarterflash, known for its saxophone-driven sound and emotive vocals.
-
D.
Make Me
"Make Me" is a song that directly precedes Janet Jackson's single "No Sleeep" in her discography.
-
E.
Make Me
"Make Me" is a 2015 thriller novel by Lee Child featuring his iconic drifter hero Jack Reacher investigating a sinister mystery in a remote American town.
- 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_69d80770b9bc81909f70c8c317d53cff |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69de01f3b46481909ceedfa78e9ca92b |
completed | April 14, 2026, 8:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d5e1ecc8190a9fec550a99702c0 |
completed | May 3, 2026, 7:09 p.m. |
Created at: April 9, 2026, 9:55 p.m.