Triple
T31418257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lenny |
E801456
|
entity |
| Predicate | dramaticStyleOfWork |
P65429
|
FINISHED |
| Object | realism |
—
|
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: realism | Statement: [Lenny, dramaticStyleOfWork, realism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dramaticStyleOfWork Context triple: [Lenny, dramaticStyleOfWork, realism]
-
A.
dramaticForm
Indicates that one entity is expressed, structured, or realized in the form of a particular dramatic genre or theatrical mode.
-
B.
dramaticRole
Indicates that one entity serves as a character or part played by another entity within a dramatic or theatrical work.
-
C.
hasDramaticStyle
chosen
Indicates that an entity employs or is characterized by a theatrical, emotionally intense, or striking manner of expression or presentation.
-
D.
dramaticCharacter
Indicates that one entity is a character or role that appears within the dramatic work, performance, or narrative represented by the other entity.
-
E.
dramaticConvention
Indicates a relationship where a particular technique, device, or practice is recognized and used as an accepted convention within dramatic or theatrical storytelling.
- 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_69f348c26f048190b4adadd71b4596c5 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a916d2e08190bafc01cba73b6469 |
completed | May 3, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69f6a7548eb48190a69b60a3c6ad53b9 |
completed | May 3, 2026, 1:39 a.m. |
Created at: April 30, 2026, 8:45 p.m.