Triple
T33184256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivan Bezdomny |
E849419
|
entity |
| Predicate | learnsStoryOf |
P104194
|
FINISHED |
| Object | The Master’s novel about Pontius Pilate |
—
|
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: The Master’s novel about Pontius Pilate | Statement: [Ivan Bezdomny, learnsStoryOf, The Master’s novel about Pontius Pilate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: learnsStoryOf Context triple: [Ivan Bezdomny, learnsStoryOf, The Master’s novel about Pontius Pilate]
-
A.
retellsStoryOf
chosen
Indicates that one entity recounts or narrates the story originally told or experienced by another entity.
-
B.
storyBy
Indicates that one entity is the creator or author of the story associated with another entity.
-
C.
originStoryIncludes
Indicates that an entity’s origin story contains, involves, or features the referenced element as a component or part of that backstory.
-
D.
storyTime
Indicates that one entity is narrating or sharing a story with another entity, typically in a designated or scheduled period for storytelling.
-
E.
originStorySummary
Indicates a brief narrative explaining how something began, was created, or came into existence.
- 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_69f3495e0f108190a6a7006f79f9c2c3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6dd3cc0648190a275812d6711275a |
completed | May 3, 2026, 5:29 a.m. |
| PD | Predicate disambiguation | batch_69f6d82eaee081908f06a71546315aea |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:29 a.m.