Triple
T8034470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pozdnyshev |
E187069
|
entity |
| Predicate | storyFrame |
P35676
|
FINISHED |
| Object | relates his life story to fellow train passengers |
—
|
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: relates his life story to fellow train passengers | Statement: [Pozdnyshev, storyFrame, relates his life story to fellow train passengers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyFrame Context triple: [Pozdnyshev, storyFrame, relates his life story to fellow train passengers]
-
A.
narrativeFrame
Indicates the overarching narrative context or perspective within which events, actions, or relationships are presented or interpreted.
-
B.
storyElement
chosen
Indicates that one entity functions as a narrative component or part within the structure of another entity’s story.
-
C.
storyline
Indicates that one entity serves as the narrative plot or sequence of events associated with another entity.
-
D.
storyFunction
Indicates that one entity serves a particular narrative role or function within the story structure of another entity.
-
E.
frameOfAction
Indicates the contextual situation, setting, or circumstances within which an action or event takes place.
- 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_69ca82ae2d1081909dbfee42b41db419 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ef50f4c8190a895ac301f182734 |
completed | March 31, 2026, 3:26 a.m. |
| PD | Predicate disambiguation | batch_69cb049688208190b32088bd2c5930bc |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:22 p.m.