Triple
T20625012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tomorrow Never Comes |
E506794
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
Hellbound Train
"Hellbound Train" is a blues-rock song best known as the dark, driving title track from Savoy Brown’s 1972 album.
|
E1441998
|
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: Hellbound Train | Statement: [Tomorrow Never Comes, hasTrack, Hellbound Train]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hellbound Train Context triple: [Tomorrow Never Comes, hasTrack, Hellbound Train]
-
A.
Hellbound
Hellbound is a South Korean dark fantasy horror series that explores supernatural judgments and societal chaos when people receive decrees of their impending damnation.
-
B.
Hellbound
Hellbound is a hard rock studio album by American band Buckcherry, known for its energetic, riff-driven sound and gritty vocals.
-
C.
Hellbound
Hellbound is a track from the Pixies' influential 1990 alternative rock album "Pod."
-
D.
Fresh Hell
Fresh Hell is a comedic web series in which actor Brent Spiner plays a fictionalized version of himself navigating a bizarre Hollywood downfall.
-
E.
Hope to Die
Hope to Die is a crime thriller novel in James Patterson’s Alex Cross series, following the detective’s desperate race to save his kidnapped family from a ruthless adversary.
- 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: Hellbound Train Triple: [Tomorrow Never Comes, hasTrack, Hellbound Train]
Generated description
"Hellbound Train" is a blues-rock song best known as the dark, driving title track from Savoy Brown’s 1972 album.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hellbound Train Target entity description: "Hellbound Train" is a blues-rock song best known as the dark, driving title track from Savoy Brown’s 1972 album.
-
A.
Hellbound
Hellbound is a South Korean dark fantasy horror series that explores supernatural judgments and societal chaos when people receive decrees of their impending damnation.
-
B.
Hellbound
Hellbound is a track from the Pixies' influential 1990 alternative rock album "Pod."
-
C.
Hellbound
Hellbound is a hard rock studio album by American band Buckcherry, known for its energetic, riff-driven sound and gritty vocals.
-
D.
Fresh Hell
Fresh Hell is a comedic web series in which actor Brent Spiner plays a fictionalized version of himself navigating a bizarre Hollywood downfall.
-
E.
Hope to Die
Hope to Die is a crime thriller novel in James Patterson’s Alex Cross series, following the detective’s desperate race to save his kidnapped family from a ruthless adversary.
- 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe490a08190b8fe49da78ebd6cc |
completed | April 20, 2026, 10:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08bb1d9fc881909afe38600d8556b1 |
completed | May 16, 2026, 6:44 p.m. |
| NEDg | Description generation | batch_6a08bbb570f4819093e23b20fd83d101 |
completed | May 16, 2026, 6:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08bf7d661c8190af9e9b7b4121f951 |
completed | May 16, 2026, 7:03 p.m. |
Created at: April 16, 2026, 11:42 a.m.