Triple
T5160130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ludaversal |
E116414
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
Money
"Money" is a track by American rapper Ludacris from his studio album *Ludaversal*.
|
E497304
|
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: Money | Statement: [Ludaversal, hasTrack, Money]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Money Context triple: [Ludaversal, hasTrack, Money]
-
A.
Money
Money is a personal finance magazine and media brand that provides advice and information on investing, saving, budgeting, and financial planning for consumers.
-
B.
Money
"Money" is a satirical comedy play by Edward Bulwer-Lytton that critiques the social power and moral influence of wealth in Victorian society.
-
C.
Money Money
"Money Money" is a classic reggae song by Jamaican singer Horace Andy, known for its socially conscious lyrics about wealth and inequality.
-
D.
Words and Money
Words and Money is a critical examination of the commercialization of publishing and the media industry by editor and publisher André Schiffrin.
-
E.
Money Talks
Money Talks is a 1997 American action-comedy film starring Chris Tucker and Charlie Sheen, known for its fast-paced humor and crime-driven plot.
- 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: Money Triple: [Ludaversal, hasTrack, Money]
Generated description
"Money" is a track by American rapper Ludacris from his studio album *Ludaversal*.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Money Target entity description: "Money" is a track by American rapper Ludacris from his studio album *Ludaversal*.
-
A.
Money
Money is a personal finance magazine and media brand that provides advice and information on investing, saving, budgeting, and financial planning for consumers.
-
B.
Money
"Money" is a satirical comedy play by Edward Bulwer-Lytton that critiques the social power and moral influence of wealth in Victorian society.
-
C.
Money Money
"Money Money" is a classic reggae song by Jamaican singer Horace Andy, known for its socially conscious lyrics about wealth and inequality.
-
D.
Words and Money
Words and Money is a critical examination of the commercialization of publishing and the media industry by editor and publisher André Schiffrin.
-
E.
Money Talks
Money Talks is a 1997 American action-comedy film starring Chris Tucker and Charlie Sheen, known for its fast-paced humor and crime-driven plot.
- 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_69bd445edb3881909b93b34d260717fc |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd790613bc819084765cd4ea648dc9 |
completed | March 20, 2026, 4:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed01ce48081908813348b762bf1b0 |
completed | March 21, 2026, 5:06 p.m. |
| NEDg | Description generation | batch_69bed08b4acc819096e7fd2fd9dbc73a |
completed | March 21, 2026, 5:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bed103a1088190abca6e7d1fbd9c2b |
completed | March 21, 2026, 5:10 p.m. |
Created at: March 20, 2026, 1:44 p.m.