Triple
T32918226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aksinia |
E842074
|
entity |
| Predicate | relationshipTypeWithGrigoriMelekhov |
P205197
|
FINISHED |
| Object | passionate love affair |
—
|
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: passionate love affair | Statement: [Aksinia, relationshipTypeWithGrigoriMelekhov, passionate love affair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithGrigoriMelekhov Context triple: [Aksinia, relationshipTypeWithGrigoriMelekhov, passionate love affair]
-
A.
relationshipTypeWithAlexeiIvanovich
Indicates the specific nature or category of relationship that an entity has with Alexei Ivanovich.
-
B.
relationshipToGrigoryOtrepiev
Indicates the nature of a person or entity’s relationship or connection to Grigory Otrepiev.
-
C.
relationshipToPolinaAlexandrovna
Indicates the specific type of personal or social relationship that one entity has with Polina Alexandrovna.
-
D.
relationshipToPavelVlasov
Indicates the nature or type of relationship an entity has with Pavel Vlasov.
-
E.
hasRelationshipTypeWithAglayaIvanovna
Indicates that an entity has a specific type of relationship or connection with Aglaya Ivanovna.
- 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_69f3494779388190a5d3e97f92278be2 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037cab06288190b093935f235ddff2 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:19 a.m.