Triple
T14966639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | USA Today |
E373204
|
entity |
| Predicate | hasSection |
P35
|
FINISHED |
| Object | Money |
E3455
|
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 | Statement: [USA Today, hasSection, Money]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Money Context triple: [USA Today, hasSection, Money]
-
A.
Money
"Money" is a well-known musical number from the stage production Cabaret that satirically explores greed and the corrupting influence of wealth.
-
B.
Money
Money is a medium of exchange and store of value used to facilitate trade, measure worth, and save wealth in economies worldwide.
-
C.
Money
"Money" is a track by Nigerian rapper Olamide from his debut studio album "YBNL," blending streetwise lyrics with Afro-hip hop production.
-
D.
Money
Money is a 1928 silent French film directed by Marcel L’Herbier, notable for its innovative visual style and critique of high finance and capitalism.
-
E.
Money
chosen
Money is a personal finance magazine and media brand that provides advice and information on investing, saving, budgeting, and financial planning for consumers.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6e2fdcc8190bffe603db3388736 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8be122688190b20fe4450786158a |
completed | May 9, 2026, 1:20 a.m. |
Created at: April 10, 2026, 2:47 a.m.