Triple
T22091435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I'd Do Anything |
E545922
|
entity |
| Predicate | relatedTo |
P37
|
FINISHED |
| Object | How Do You Solve a Problem like Maria? |
—
|
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: How Do You Solve a Problem like Maria? | Statement: [I'd Do Anything, relatedTo, How Do You Solve a Problem like Maria?]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: How Do You Solve a Problem like Maria? Context triple: [I'd Do Anything, relatedTo, How Do You Solve a Problem like Maria?]
-
A.
“How Do You Solve a Problem Like Maria?”
chosen
“How Do You Solve a Problem Like Maria?” is a lively song from the musical *The Sound of Music* in which the nuns humorously debate the unconventional nature of the novice Maria.
-
B.
Mornings with Maria
Mornings with Maria is a weekday morning business and news talk show hosted by Maria Bartiromo on the Fox Business Network.
-
C.
I Got a Problem
"I Got a Problem" is a song featured on the album "Lucky Thirteen."
-
D.
Mama
"Mama" is a song by the Japanese rock band Boi-ngo.
-
E.
Mama
"Mama" is an indie pop song by Coconut Records, the solo music project of actor and musician Jason Schwartzman.
- 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_69e11e36d03c8190a83a1ba802b7231b |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128e5edf08190a6743955bc872417 |
completed | April 28, 2026, 9:38 p.m. |
Created at: April 16, 2026, 8:29 p.m.