Triple
T20524720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sum 41 |
E503904
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Out for Blood
Out for Blood is a song by Canadian rock band Sum 41, known for its aggressive punk-influenced sound and themes of anger and rebellion.
|
E1435956
|
NE FINISHED |
How this triple was built (4 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: Out for Blood | Statement: [Sum 41, notableWork, Out for Blood]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Out for Blood Context triple: [Sum 41, notableWork, Out for Blood]
-
A.
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*.
-
B.
The Blood & Tears
The Blood & Tears is a track by guitarist Steve Vai featured on his album "The Ultra Zone."
-
C.
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.
-
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.
Dark Blood
Dark Blood is a crime thriller novel by Scottish author Stuart MacBride, featuring Detective Sergeant Logan McRae in a gritty Aberdeen-set investigation.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Out for Blood Triple: [Sum 41, notableWork, Out for Blood]
Generated description
Out for Blood is a song by Canadian rock band Sum 41, known for its aggressive punk-influenced sound and themes of anger and rebellion.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Out for Blood Target entity description: Out for Blood is a song by Canadian rock band Sum 41, known for its aggressive punk-influenced sound and themes of anger and rebellion.
-
A.
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*.
-
B.
The Blood & Tears
The Blood & Tears is a track by guitarist Steve Vai featured on his album "The Ultra Zone."
-
C.
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.
-
D.
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.
-
E.
Dark Blood
Dark Blood is a crime thriller novel by Scottish author Stuart MacBride, featuring Detective Sergeant Logan McRae in a gritty Aberdeen-set investigation.
- F. None of above. chosen
Provenance (5 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_69e0b4b3a6e08190ae663701f50fab8e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e69f48691c8190af0ac959e92e10d9 |
completed | April 20, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a089d43c6588190a4be58521ca67698 |
completed | May 16, 2026, 4:37 p.m. |
| NEDg | Description generation | batch_6a089e00cde081908dca3893f03e3398 |
completed | May 16, 2026, 4:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a089e8a05488190b3470f4ffb5927ce |
completed | May 16, 2026, 4:42 p.m. |
Created at: April 16, 2026, 11:37 a.m.