Triple
T8988793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | So Help Me God! |
E214734
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Money Maker |
E116422
|
NE FINISHED |
How this triple was built (2 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 Maker | Statement: [So Help Me God!, hasTrack, Money Maker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Money Maker Context triple: [So Help Me God!, hasTrack, Money Maker]
-
A.
Money Maker
chosen
"Money Maker" is a popular hip hop single by Ludacris featuring Pharrell, known for its club-friendly beat and commercial success in the mid-2000s.
-
B.
Got Money
"Got Money" is a popular hip-hop single by Lil Wayne featuring T-Pain, known for its club-oriented sound and commercial success in the late 2000s.
-
C.
Millionaire
"Millionaire" is a 2004 R&B/hip-hop single by American singer Kelis featuring André 3000, known for its laid-back groove and distinctive production.
-
D.
Millionaire
"Millionaire" is a song by the English rock band Beady Eye, formed by former members of Oasis.
-
E.
The Millionaire
The Millionaire is a 1931 American pre-Code comedy film starring George Arliss as a retired businessman who secretly returns to work, produced by Warner Bros. and associated with filmmaker Bryan Foy.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca839f76bc8190a4b7123cdd682199 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc67f0fed8819098ef3c88f9ef8045 |
completed | April 1, 2026, 12:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0c58c94819095979b82a50cb77d |
completed | April 3, 2026, 2:37 p.m. |
Created at: March 30, 2026, 7:04 p.m.