Triple
T19665419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tempest |
E472186
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Pay in Blood |
—
|
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: Pay in Blood | Statement: [Tempest, hasTrack, Pay in Blood]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pay in Blood Context triple: [Tempest, hasTrack, Pay in Blood]
-
A.
Pay in Blood
chosen
"Pay in Blood" is a dark, hard-edged song by Bob Dylan from his 2012 album *Tempest*, noted for its violent biblical imagery and bitter, vengeful tone.
-
B.
Blood to Bleed
"Blood to Bleed" is a song by the American punk rock band Rise Against from their album *Siren Song of the Counter Culture*.
-
C.
Back to Blood
Back to Blood is a 2012 novel by Tom Wolfe that satirically explores race, class, and immigrant life in contemporary Miami.
-
D.
I’m Blooded
"I’m Blooded" is a track featured on the album "Dedication 2" by Lil Wayne and DJ Drama.
-
E.
In the Blood
"In the Blood" is a reflective pop-rock song by John Mayer that explores themes of identity and inherited traits, featured on his 2017 album *The Search for Everything*.
- 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_69d8e514f2e08190ba70a4449519d218 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6416857c88190acb3adbf3e585fe5 |
completed | April 20, 2026, 3:08 p.m. |
Created at: April 10, 2026, 1:45 p.m.