Triple
T22741296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramones – Too Tough to Die |
E562420
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Mama’s Boy |
—
|
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: Mama’s Boy | Statement: [Ramones – Too Tough to Die, hasPart, Mama’s Boy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mama’s Boy Context triple: [Ramones – Too Tough to Die, hasPart, Mama’s Boy]
-
A.
Mama's Boy
chosen
"Mama's Boy" is a track from the Ramones' 1984 punk rock album "Too Tough to Die."
-
B.
Mama's Boy
"Mama's Boy" is a 2007 comedy film starring Jon Heder as an immature adult struggling to grow up when his widowed mother starts dating again.
-
C.
Mama’s Boyfriend
"Mama’s Boyfriend" is an unreleased Kanye West track, known among fans as a scrapped song from the My Beautiful Dark Twisted Fantasy era that circulated in demo and live-performance form.
-
D.
Mama’s Love
"Mama’s Love" is a song featured on the album *Epistles of Mama*, likely reflecting themes of maternal affection and tribute.
-
E.
Mama’s Gun
Mama’s Gun is a critically acclaimed neo-soul album by Erykah Badu, known for its warm, live instrumentation and introspective, socially conscious songwriting.
- 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_69e245513a5c81908d5cb471b4fc429d |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17972fde8819086094cea289a2af8 |
completed | April 29, 2026, 3:22 a.m. |
Created at: April 17, 2026, 3:23 p.m.