Triple
T16672789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wolves |
E405145
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
Mourning in Amerika
"Mourning in Amerika" is a politically charged punk rock song by the American band Wolves in the Throne Room.
|
E1226990
|
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: Mourning in Amerika | Statement: [Wolves, hasTrack, Mourning in Amerika]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mourning in Amerika Context triple: [Wolves, hasTrack, Mourning in Amerika]
-
A.
The Mourner
The Mourner is a Japanese film in which Kengo Kora stars in a contemplative drama about grief, guilt, and spiritual redemption.
-
B.
A Night This Side of Dying
"A Night This Side of Dying" is a song by Carole King featured on her 1974 album *Wrap Around Joy*.
-
C.
Ameriican Requiem
"Ameriican Requiem" is a song by Beyoncé from her genre-blending, country-influenced album "Cowboy Carter."
-
D.
Mourning in the Morning
"Mourning in the Morning" is a 1969 electric blues album by guitarist and singer Otis Rush that blends Chicago blues with soul and rock influences.
-
E.
A Funeral
"A Funeral" is a somber interior painting by Danish artist Anna Ancher that reflects her characteristic use of light and color to depict everyday life in Skagen.
- 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: Mourning in Amerika Triple: [Wolves, hasTrack, Mourning in Amerika]
Generated description
"Mourning in Amerika" is a politically charged punk rock song by the American band Wolves in the Throne Room.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mourning in Amerika Target entity description: "Mourning in Amerika" is a politically charged punk rock song by the American band Wolves in the Throne Room.
-
A.
The Mourner
The Mourner is a Japanese film in which Kengo Kora stars in a contemplative drama about grief, guilt, and spiritual redemption.
-
B.
A Night This Side of Dying
"A Night This Side of Dying" is a song by Carole King featured on her 1974 album *Wrap Around Joy*.
-
C.
Ameriican Requiem
"Ameriican Requiem" is a song by Beyoncé from her genre-blending, country-influenced album "Cowboy Carter."
-
D.
Mourning in the Morning
"Mourning in the Morning" is a 1969 electric blues album by guitarist and singer Otis Rush that blends Chicago blues with soul and rock influences.
-
E.
A Funeral
"A Funeral" is a somber interior painting by Danish artist Anna Ancher that reflects her characteristic use of light and color to depict everyday life in Skagen.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ca276848190b7562d7cb88d21e0 |
completed | April 18, 2026, 12:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a3916508190bd5edd91310ddb5a |
completed | May 10, 2026, 1:38 p.m. |
| NEDg | Description generation | batch_6a008b001c988190b0ddec3be0ed6fd0 |
completed | May 10, 2026, 1:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a008b9a8b6481909df37edcecdd292c |
completed | May 10, 2026, 1:43 p.m. |
Created at: April 10, 2026, 5:19 a.m.