Triple
T7076075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Dmitrievna Isaeva |
E164821
|
entity |
| Predicate | relationshipToFyodorDostoevsky |
P38921
|
FINISHED |
| Object | emotional dependence |
—
|
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: emotional dependence | Statement: [Maria Dmitrievna Isaeva, relationshipToFyodorDostoevsky, emotional dependence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToFyodorDostoevsky Context triple: [Maria Dmitrievna Isaeva, relationshipToFyodorDostoevsky, emotional dependence]
-
A.
relationshipToPierreBezukhov
Indicates the specific type of personal or social relationship an entity has to Pierre Bezukhov.
-
B.
relationshipToCharacter
chosen
Indicates the specific type of personal, social, or narrative connection that one entity has to a given character.
-
C.
roleInWarAndPeace
Indicates that an entity has a specific role or function within the context of the War and Peace conflict or narrative.
-
D.
relatedCharacter
Indicates that one character has a specified relationship or association with another character.
-
E.
fictionalRelationship
Indicates a relationship that exists only within a fictional or imagined context between entities.
- 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_69c6887cbc6c8190bdfac42d940f4d8a |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4ebf4048190bf5d7156817f93a7 |
completed | March 27, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bfcb948190a5ada74fb8c054cb |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:40 p.m.