Triple
T10621916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Warm Up |
E250221
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
The Badness
"The Badness" is a track from the hip-hop mixtape "The Warm Up" by rapper J. Cole.
|
E875659
|
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: The Badness | Statement: [The Warm Up, hasTrack, The Badness]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Badness Context triple: [The Warm Up, hasTrack, The Badness]
-
A.
Bad Is Bad
"Bad Is Bad" is a rock song by Huey Lewis and the News, featured on their hit 1983 album "Sports."
-
B.
The Bad Place
"The Bad Place" is a horror-thriller novel by Dean Koontz that follows a man with amnesia and terrifying supernatural abilities as he and a married team of private investigators uncover dark secrets about his past.
-
C.
The Maddening
The Maddening is a 1995 psychological thriller film starring Burt Reynolds as a deranged patriarch who imprisons a young woman and her family.
-
D.
Good to Be Bad
Good to Be Bad is a 2008 hard rock studio album by British band Whitesnake, marking their return with new material after a long hiatus.
-
E.
Very Bad Things
Very Bad Things is a 1998 dark comedy film about a bachelor party in Las Vegas that spirals into chaos after a tragic accident leads to increasingly desperate cover-ups.
- 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: The Badness Triple: [The Warm Up, hasTrack, The Badness]
Generated description
"The Badness" is a track from the hip-hop mixtape "The Warm Up" by rapper J. Cole.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: The Badness Target entity description: "The Badness" is a track from the hip-hop mixtape "The Warm Up" by rapper J. Cole.
-
A.
Bad Is Bad
"Bad Is Bad" is a rock song by Huey Lewis and the News, featured on their hit 1983 album "Sports."
-
B.
The Bad Place
"The Bad Place" is a horror-thriller novel by Dean Koontz that follows a man with amnesia and terrifying supernatural abilities as he and a married team of private investigators uncover dark secrets about his past.
-
C.
The Maddening
The Maddening is a 1995 psychological thriller film starring Burt Reynolds as a deranged patriarch who imprisons a young woman and her family.
-
D.
Good to Be Bad
Good to Be Bad is a 2008 hard rock studio album by British band Whitesnake, marking their return with new material after a long hiatus.
-
E.
Very Bad Things
Very Bad Things is a 1998 dark comedy film about a bachelor party in Las Vegas that spirals into chaos after a tragic accident leads to increasingly desperate cover-ups.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df7e5074819096668b53dcc9167a |
completed | April 8, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96b908e788190bc9e4f327e871a7f |
completed | April 10, 2026, 9:28 p.m. |
| NEDg | Description generation | batch_69d96def8bfc81909d6a5addf724691b |
completed | April 10, 2026, 9:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d96fedb18881908570593856f4aade |
completed | April 10, 2026, 9:47 p.m. |
Created at: April 8, 2026, 8:50 p.m.