Triple
T6738685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Coasters |
E154022
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Young Blood |
E310549
|
NE FINISHED |
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: Young Blood | Statement: [The Coasters, notableWork, Young Blood]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Young Blood Context triple: [The Coasters, notableWork, Young Blood]
-
A.
Young Blood
chosen
"Young Blood" is a classic rhythm and blues song from the 1950s, best known in its hit version by The Coasters and widely covered in rock and roll history.
-
B.
Youngblood
"Youngblood" is a song by American punk rock band Green Day from their 2016 album *Revolution Radio*.
-
C.
I’m Blooded
"I’m Blooded" is a track featured on the album "Dedication 2" by Lil Wayne and DJ Drama.
-
D.
Bloods
Bloods is a predominantly African-American street gang that originated in Los Angeles and is known for its rivalry with the Crips and its nationwide network of affiliated sets.
-
E.
Bloods
Bloods is a popular nickname for the Sydney Swans, an Australian Football League club known for its red-and-white colors and strong team culture.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c6880d84d8819095d19de2295f26ac |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1866dbc81909483fbd5ed6a3ec8 |
completed | March 27, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c70b0b97248190bf6bac160fe3d45b |
completed | March 27, 2026, 10:56 p.m. |
Created at: March 27, 2026, 2:10 p.m.