Triple
T33352660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beniowski |
E853985
|
entity |
| Predicate | fictionalizedSubject |
P3171
|
FINISHED |
| Object | Maurice Benyovszky |
—
|
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: Maurice Benyovszky | Statement: [Beniowski, fictionalizedSubject, Maurice Benyovszky]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalizedSubject Context triple: [Beniowski, fictionalizedSubject, Maurice Benyovszky]
-
A.
fictionalPersonaOf
Indicates that one entity is a fictional or narrative persona, alter ego, or character representation of another (typically real or primary) entity.
-
B.
fictionalCharacter
Indicates that one entity is a fictional character that appears within the narrative world of another entity (such as a work, series, or franchise).
-
C.
fictionalizationOf
chosen
Indicates that one entity is a fictional or dramatized representation, adaptation, or reimagining of another (typically real or earlier) entity or event.
-
D.
fictionalSon
Indicates that one entity is portrayed as the son of another entity within a fictional or narrative context.
-
E.
fictionalCharacterAssisted
Indicates that one fictional character provided help, support, or assistance to another fictional character.
- 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_69f3496acbc8819099fd0305ecc42080 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe629b4fa481908467c7c41b77f0c6 |
completed | May 8, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69fe61bb260c819083f9378a3a06ca47 |
completed | May 8, 2026, 10:20 p.m. |
Created at: May 1, 2026, 1:34 a.m.