Triple
T23295090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alex Brown |
E590144
|
entity |
| Predicate | work |
P12692
|
FINISHED |
| Object | "All for Love" |
—
|
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: "All for Love" | Statement: [Alex Brown, work, "All for Love"]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: "All for Love" Context triple: [Alex Brown, work, "All for Love"]
-
A.
"All for Love"
chosen
"All for Love" is a song written and produced by Rick Timas, best known as a late-1980s R&B track recorded by the group Color Me Badd.
-
B.
All in Love Is Fair
All in Love Is Fair is a soulful ballad by Stevie Wonder, known for its poignant lyrics about the complexities of love and its expressive vocal and piano performance.
-
C.
For Love’s Sake
For Love’s Sake is a song by American country artist Dwight Yoakam, featured on his 2000 album "Tomorrow’s Sounds Today."
-
D.
“Woman in Love”
“Woman in Love” is a song featured within the musical work or album “Green Man.”
-
E.
Do For Love
"Do For Love" is a song by Canadian singer-songwriter and producer Black Atlass, showcasing his atmospheric blend of R&B, electronic, and alternative influences.
- 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_69e25d1af9d88190a0b9b5e8fa608618 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f196cdce7081908ca1cf9107b87f61 |
completed | April 29, 2026, 5:27 a.m. |
Created at: April 17, 2026, 5:03 p.m.