Triple
T24173907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Varvara Dobrosyolova |
E599221
|
entity |
| Predicate | relationshipToMakarDevushkin |
P155579
|
FINISHED |
| Object | close friend |
—
|
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: close friend | Statement: [Varvara Dobrosyolova, relationshipToMakarDevushkin, close friend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMakarDevushkin Context triple: [Varvara Dobrosyolova, relationshipToMakarDevushkin, close friend]
-
A.
relationshipToPolinaAlexandrovna
Indicates the specific type of personal or social relationship that one entity has with Polina Alexandrovna.
-
B.
relationshipToMadameKhokhlakova
Indicates the nature or type of relationship an entity has with Madame Khokhlakova.
-
C.
relationshipToPavelVlasov
Indicates the nature or type of relationship an entity has with Pavel Vlasov.
-
D.
relationshipTypeWithAlexeiIvanovich
Indicates the specific nature or category of relationship that an entity has with Alexei Ivanovich.
-
E.
hasRelationshipTypeWithNastasyaFilippovna
Indicates that an entity has a specific type of relationship with Nastasya Filippovna.
- F. None of above. chosen
Provenance (4 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_69e288cca05481908faeb1563711114a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9ddfcc819096697a844b300cce |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f27a753ca8819095706970d368f762 |
completed | April 29, 2026, 9:39 p.m. |
Created at: April 17, 2026, 11:33 p.m.