Triple
T14679183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Zolanski |
E344730
|
entity |
| Predicate | hasNotableQuoteStyle |
P84095
|
FINISHED |
| Object | rapid, exaggerated delivery |
—
|
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: rapid, exaggerated delivery | Statement: [Roman Zolanski, hasNotableQuoteStyle, rapid, exaggerated delivery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableQuoteStyle Context triple: [Roman Zolanski, hasNotableQuoteStyle, rapid, exaggerated delivery]
-
A.
notableQuoteStyle
chosen
Indicates the characteristic manner or style in which a notable quote is expressed or delivered.
-
B.
hasCatchphraseStyle
Indicates that an entity’s catchphrase conforms to, or is characterized by, a particular stylistic pattern or manner of expression.
-
C.
hasNotablePhrase
Indicates that an entity is associated with a specific phrase or expression that is considered notable or characteristic of it.
-
D.
hasNotableSentence
Indicates that an entity is associated with a particularly important, famous, or otherwise noteworthy sentence.
-
E.
notableQuote
Indicates that one entity is a significant or well-known quotation attributed to, recorded by, or strongly associated with another entity.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb5692284819090f775be8e478522 |
completed | April 14, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69de6579fb7881909becc8f5822b39d4 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:27 a.m.