Triple
T16133954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David di Donatello for Best Actress |
E391471
|
entity |
| Predicate | typeOfRoleRecognized |
P5518
|
FINISHED |
| Object | leading role in a feature film |
—
|
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: leading role in a feature film | Statement: [David di Donatello for Best Actress, typeOfRoleRecognized, leading role in a feature film]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfRoleRecognized Context triple: [David di Donatello for Best Actress, typeOfRoleRecognized, leading role in a feature film]
-
A.
typeOfRole
chosen
Indicates that one entity specifies the kind or category of role that another entity holds or performs.
-
B.
definesRole
Indicates that one entity specifies or establishes the role, function, or position of another entity within a given context.
-
C.
identificationRole
Indicates that an entity serves as an identifier or plays a role in uniquely distinguishing or recognizing another entity.
-
D.
acknowledgesRoleOf
Indicates that one entity explicitly recognizes and accepts the position, function, or authority that another entity holds.
-
E.
possibleRole
Indicates that an entity is capable of or eligible to serve in a particular role or function in a given 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21a039f0c8190a679e16a27f2dbe3 |
completed | April 17, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69e182885bc08190822ae7e8a4b8ac1f |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:01 a.m.