Triple
T28332318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Il turco in Italia |
E717567
|
entity |
| Predicate | hasMetaTheatricalCharacter |
P12417
|
FINISHED |
| Object | Prosdocimo |
—
|
NE NERFINISHED |
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: Prosdocimo | Statement: [Il turco in Italia, hasMetaTheatricalCharacter, Prosdocimo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMetaTheatricalCharacter Context triple: [Il turco in Italia, hasMetaTheatricalCharacter, Prosdocimo]
-
A.
metCharacter
Indicates that one entity has encountered or been introduced to another entity at least once.
-
B.
hasMetafictionalRole
chosen
Indicates that an entity plays a role within a story that self-consciously comments on, references, or breaks the conventions of fiction itself.
-
C.
hasFictionalCoStar
Indicates that one entity appears as a co-star alongside another entity within a fictional work or narrative.
-
D.
hasFictionalPerformer
Indicates that an entity is associated with a performer who is a fictional or imaginary character rather than a real person.
-
E.
hasFictionalRole
Indicates that an entity plays or is assigned a specific role within a fictional work or narrative.
- 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_69eff6e9a57c8190a69c2c74b5d72119 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69fbc9d1dba881908c399b8e1dc13ce2 |
completed | May 6, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ec03ac8190a757563f96fab283 |
completed | May 6, 2026, 11:04 p.m. |
Created at: April 28, 2026, 12:33 a.m.