Triple
T5454077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "Not with a bang but a whimper" |
E122436
|
entity |
| Predicate | quotationSourceAuthorNationality |
P6689
|
FINISHED |
| Object | British-American |
—
|
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: British-American | Statement: ["Not with a bang but a whimper", quotationSourceAuthorNationality, British-American]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: quotationSourceAuthorNationality Context triple: ["Not with a bang but a whimper", quotationSourceAuthorNationality, British-American]
-
A.
notableQuoteTranslation
Indicates that one quote is a translation of another quote, preserving its meaning across different languages.
-
B.
quoteAttributedTo
Indicates that a specific quotation is credited as having been said or written by a particular source or entity.
-
C.
notableQuote
Indicates that one entity is a significant or well-known quotation attributed to, recorded by, or strongly associated with another entity.
-
D.
authorNationality
chosen
Indicates the relationship between an author and the country or nationality with which that author is identified.
-
E.
quotedOn
Indicates that one entity is cited, referenced, or mentioned within another source, document, or context.
- 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_69bd46424248819085282ddf50a565f3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd927c946c8190aef40679199fede3 |
completed | March 20, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69bd91a0d96c8190bd1299edbf764bbb |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:08 p.m.