Triple
T23785385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arkady Svidrigailov |
E587935
|
entity |
| Predicate | hasPsychologicalImpactOn |
P102027
|
FINISHED |
| Object | Rodion Raskolnikov |
—
|
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: Rodion Raskolnikov | Statement: [Arkady Svidrigailov, hasPsychologicalImpactOn, Rodion Raskolnikov]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPsychologicalImpactOn Context triple: [Arkady Svidrigailov, hasPsychologicalImpactOn, Rodion Raskolnikov]
-
A.
hasPsychologicalCondition
Indicates that an entity experiences or is diagnosed with a particular psychological or mental health condition.
-
B.
hasPsychologicalDepth
Indicates that an entity (such as a work, character, or portrayal) exhibits complex, nuanced inner life, motivations, and emotions that invite deeper psychological interpretation.
-
C.
canImpact
Indicates that one entity has the potential or ability to affect, influence, or cause a change in another entity.
-
D.
recognizesImpactOn
Indicates that one entity acknowledges or understands the effect or consequences it has on another entity or situation.
-
E.
impactOnSubject
chosen
Indicates the effect, influence, or consequence that one entity, event, or action has on a specified subject.
- 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_69e2490f4ad48190b690878eec3596c6 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1c630f81c81909413ba06ae27ebfc |
completed | April 29, 2026, 8:49 a.m. |
| PD | Predicate disambiguation | batch_69f155fe300481909bd617443228df65 |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:17 p.m.