Triple
T20178778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ¡Dos! |
E492669
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Lazy Bones |
—
|
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: Lazy Bones | Statement: [¡Dos!, hasTrack, Lazy Bones]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lazy Bones Context triple: [¡Dos!, hasTrack, Lazy Bones]
-
A.
Lazy Bones
chosen
"Lazy Bones" is a song by the American punk rock band Green Day, featured on their 2012 album ¡Dos!.
-
B.
Skinny Bones
Skinny Bones is the stage name of Garrett Uhlenbrock, an American songwriter and musician best known for his work with the Ramones.
-
C.
Pass the Bone
"Pass the Bone" is a track by the hip-hop group Gang Starr, known for its classic boom-bap production and Guru's smooth, intricate lyricism.
-
D.
Monkeybone
Monkeybone is a 2001 dark fantasy–comedy film that blends live action and animation in a surreal story about a cartoonist trapped in a bizarre dream world.
-
E.
Two Bones
Two Bones is a hard bop jazz album led by trombonist Curtis Fuller, noted for its tight ensemble work and classic late-1950s Blue Note sound.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e668ed07c8819091bd9ffda237a91c |
completed | April 20, 2026, 5:57 p.m. |
Created at: April 11, 2026, 11:36 p.m.