Triple
T21449791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Come What May |
E529176
|
entity |
| Predicate | hasTitle |
P38
|
FINISHED |
| Object | Come What May |
—
|
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: Come What May | Statement: [Come What May, hasTitle, Come What May]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Come What May Context triple: [Come What May, hasTitle, Come What May]
-
A.
Come What May
chosen
"Come What May" is a romantic ballad famously associated with Baz Luhrmann’s film Moulin Rouge!, serving as one of its central love themes.
-
B.
Come What May
"Come What May" is a popular song co-written by Carole Bayer Sager, known for its romantic theme and enduring appeal in pop and adult contemporary music.
-
C.
You May Be Right
"You May Be Right" is a 1980 rock song by American singer-songwriter Billy Joel, known for its driving rhythm, self-deprecating lyrics, and status as one of his signature hits.
-
D.
Oh Yes
"Oh Yes" is a song featured on Whitney Houston’s 1998 R&B/pop album *My Love Is Your Love*.
-
E.
She Will
"She Will" is a hip-hop song by Lil Wayne featuring Drake, known for its moody production and introspective lyrics about success, loyalty, and relationships.
- 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_69e0c457579481909db68053ed99750c |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9d281c0819080c3f8a58947a115 |
completed | April 23, 2026, 9:43 a.m. |
Created at: April 16, 2026, 6:06 p.m.