Triple
T19012790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gremin |
E465268
|
entity |
| Predicate | treatmentOfTatyana |
P85256
|
FINISHED |
| Object | deeply respectful and loving |
—
|
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: deeply respectful and loving | Statement: [Gremin, treatmentOfTatyana, deeply respectful and loving]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatmentOfTatyana Context triple: [Gremin, treatmentOfTatyana, deeply respectful and loving]
-
A.
treatmentOf
Indicates a relationship where one entity administers, provides, or is responsible for a therapeutic intervention directed toward another entity (typically a patient or condition).
-
B.
relationshipTypeWithTaniaFedorova
Indicates the specific nature or category of relationship that an entity has with Tania Fedorova.
-
C.
treatmentOfCinderella
chosen
Indicates how one party behaves toward or deals with Cinderella.
-
D.
subjectTreatment
Indicates that a subject is receiving, undergoing, or being administered a particular treatment or therapeutic intervention.
-
E.
treatmentType
Indicates the specific kind or category of treatment applied or prescribed in relation to an entity or condition.
- 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_69d8dd025c188190a1d81f5b4ec7e2c6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d6a9bac8819093f9af57000667b0 |
completed | April 20, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69e4a2fd80c081908237317a3a883e1c |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 12:02 p.m.