Triple
T23462750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fantastic, Vol. 2 |
E569024
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | “Fall in 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: “Fall in Love” | Statement: [Fantastic, Vol. 2, hasPart, “Fall in Love”]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: “Fall in Love” Context triple: [Fantastic, Vol. 2, hasPart, “Fall in Love”]
-
A.
“Fallin’ for You”
“Fallin’ for You” is an R&B song written and produced by Shep Crawford, best known for its smooth, emotive style and soulful vocal delivery.
-
B.
Fall in Love
"Fall in Love" is a popular Afrobeat love song by Nigerian artist D'banj that became one of his signature hits across Africa.
-
C.
Fall in Love
"Fall in Love" is a breakout hip-hop/R&B single by American rapper GoldLink that showcases his melodic flow over a danceable, groove-driven production.
-
D.
Fall in Love
"Fall in Love" is an R&B single by American singer Keke Wyatt that showcases her powerful vocals and emotive, soulful style.
-
E.
Fall in Love
"Fall in Love" is an episode of the American sitcom *The King of Queens*, featuring the comedic misadventures of Doug and Carrie Heffernan in Queens, New York.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69e2458ebd808190b3298163132cfb0b |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a69cf7c48190b4d44e500f955b99 |
completed | April 29, 2026, 6:35 a.m. |
Created at: April 17, 2026, 5:54 p.m.