Triple
T21681337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nozdryov |
E535114
|
entity |
| Predicate | relationshipTypeWithPavel Chichikov |
P145426
|
FINISHED |
| Object | acquaintance |
—
|
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: acquaintance | Statement: [Nozdryov, relationshipTypeWithPavel Chichikov, acquaintance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithPavel Chichikov Context triple: [Nozdryov, relationshipTypeWithPavel Chichikov, acquaintance]
-
A.
relationshipToPavelVlasov
Indicates the nature or type of relationship an entity has with Pavel Vlasov.
-
B.
relationshipToPolinaAlexandrovna
Indicates the specific type of personal or social relationship that one entity has with Polina Alexandrovna.
-
C.
relationshipToOnegin
Indicates the specific interpersonal or familial relationship that one entity has to the person named Onegin.
-
D.
relationshipToPierreBezukhov
Indicates the specific type of personal or social relationship an entity has to Pierre Bezukhov.
-
E.
relationshipToTatyanaLarina
Indicates the specific personal or social connection that an entity has to Tatyana Larina.
- 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_69e0c469b6ec8190aee4cadd1527db91 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef96c69990819088a1134ecea09099 |
completed | April 27, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69e6968abfdc81909cf9e0bd72db9eca |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69cb4bcbc8190a4fc2d508df107be |
completed | April 20, 2026, 9:37 p.m. |
Created at: April 16, 2026, 6:43 p.m.