Triple
T11294516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danish trade unions |
E267415
|
entity |
| Predicate | include |
P1393
|
FINISHED |
| Object |
Dansk Metal
Dansk Metal is a major Danish trade union representing workers primarily in the metal, engineering, and industrial sectors.
|
E917693
|
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: Dansk Metal | Statement: [Danish trade unions, include, Dansk Metal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dansk Metal Context triple: [Danish trade unions, include, Dansk Metal]
-
A.
Dokken
Dokken is an American heavy metal band, best known for its melodic, guitar-driven sound and popularity during the 1980s glam metal era.
-
B.
Amon Amarth
Amon Amarth is the fiery volcanic mountain in J.R.R. Tolkien’s Middle-earth where the One Ring is ultimately destroyed.
-
C.
In Flames
In Flames is a pioneering Swedish metal band widely credited with shaping the Gothenburg melodic death metal sound and influencing modern metal worldwide.
-
D.
Krallice
Krallice is an American experimental black metal band known for its complex, highly technical compositions and involvement in the New York avant‑metal scene.
-
E.
HammerFall
HammerFall is a Swedish power metal band known for helping revive traditional heavy metal in the late 1990s with melodic, anthem-driven songs and fantasy-themed imagery.
- 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: Dansk Metal Triple: [Danish trade unions, include, Dansk Metal]
Generated description
Dansk Metal is a major Danish trade union representing workers primarily in the metal, engineering, and industrial sectors.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dansk Metal Target entity description: Dansk Metal is a major Danish trade union representing workers primarily in the metal, engineering, and industrial sectors.
-
A.
Dokken
Dokken is an American heavy metal band, best known for its melodic, guitar-driven sound and popularity during the 1980s glam metal era.
-
B.
Amon Amarth
Amon Amarth is the fiery volcanic mountain in J.R.R. Tolkien’s Middle-earth where the One Ring is ultimately destroyed.
-
C.
In Flames
In Flames is a pioneering Swedish metal band widely credited with shaping the Gothenburg melodic death metal sound and influencing modern metal worldwide.
-
D.
Krallice
Krallice is an American experimental black metal band known for its complex, highly technical compositions and involvement in the New York avant‑metal scene.
-
E.
HammerFall
HammerFall is a Swedish power metal band known for helping revive traditional heavy metal in the late 1990s with melodic, anthem-driven songs and fantasy-themed imagery.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e98b149481909f432a6b9ef8bfbb |
completed | April 9, 2026, 6:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e50a32ac308190828e1138522527fb |
completed | April 19, 2026, 5 p.m. |
| NEDg | Description generation | batch_69e510f9edb4819097e9fa1ce85504ed |
completed | April 19, 2026, 5:29 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e516ac8dec81909c9c1eece372189e |
completed | April 19, 2026, 5:53 p.m. |
Created at: April 8, 2026, 9:32 p.m.