Triple
T8315127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andy Dufresne |
E194686
|
entity |
| Predicate | favoriteSaying |
P33455
|
FINISHED |
| Object | Get busy living, or get busy dying |
—
|
LITERAL 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: Get busy living, or get busy dying | Statement: [Andy Dufresne, favoriteSaying, Get busy living, or get busy dying]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: favoriteSaying Context triple: [Andy Dufresne, favoriteSaying, Get busy living, or get busy dying]
-
A.
relatedProverb
Indicates that one entity is a proverb that is thematically or conceptually related to another entity.
-
B.
keySaying
chosen
Indicates that an entity is a notable or characteristic saying, phrase, or quotation associated with another entity.
-
C.
motto
Indicates that one entity serves as the guiding phrase, slogan, or maxim associated with another entity.
-
D.
notableQuote
Indicates that one entity is a significant or well-known quotation attributed to, recorded by, or strongly associated with another entity.
-
E.
associatedWithFamousSlogan
Indicates that an entity is connected to, known for, or commonly linked with a particular famous slogan.
- F. None of above.
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_69ca82e6e2648190a31eaf6f4f757b2a |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7f540b2081908ccb1b2ed040c74e |
completed | March 31, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69cb70bf689c8190a9d9b6b872abf53d |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:55 p.m.