Triple
T6507340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Perfect Harmony |
E150042
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Cash |
E117340
|
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: Cash | Statement: [Perfect Harmony, character, Cash]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cash Context triple: [Perfect Harmony, character, Cash]
-
A.
Cash
chosen
Cash is a common English surname most famously associated with legendary American singer-songwriter Johnny Cash.
-
B.
Kassa
Kassa is the historical Hungarian name for the city now known as Košice in eastern Slovakia.
-
C.
Apple Cash
Apple Cash is a digital peer-to-peer payment service by Apple that lets users send, receive, and store money on their Apple devices for use in apps, online, and in stores.
-
D.
Money
"Money" is a satirical comedy play by Edward Bulwer-Lytton that critiques the social power and moral influence of wealth in Victorian society.
-
E.
Money
"Money" is a well-known musical number from the stage production Cabaret that satirically explores greed and the corrupting influence of wealth.
- 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_69c687ef291081909d437f035eef1cda |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6996818c881909d036f916da0efb5 |
completed | March 27, 2026, 2:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cb519b8081908db92ab57ad6e871 |
completed | March 27, 2026, 6:24 p.m. |
Created at: March 27, 2026, 1:43 p.m.