Triple
T22370437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Solyony |
E553024
|
entity |
| Predicate | romanticRivalFor |
P115860
|
FINISHED |
| Object | Irina Prozorova |
—
|
NE NERFINISHED |
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: Irina Prozorova | Statement: [Solyony, romanticRivalFor, Irina Prozorova]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: romanticRivalFor Context triple: [Solyony, romanticRivalFor, Irina Prozorova]
-
A.
romanticRivalryWith
chosen
Indicates a mutual competitive relationship in which two entities vie for the romantic attention or affection of the same person.
-
B.
romanticallyObsessedWith
Indicates a strong, often overwhelming romantic fixation or preoccupation that one entity has toward another.
-
C.
hasRomanticTensionWith
Indicates a mutual or one-sided romantic attraction or unresolved romantic interest existing between two entities.
-
D.
literaryRelationship
Indicates a relationship between entities that are connected through literature, such as authorship, influence, adaptation, or other text-based associations.
-
E.
fictionalRivalOf
Indicates a rivalry relationship that exists between two entities only within a fictional or narrative context.
- 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_69e11e4c03248190a26a5060ea6973ee |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15803e7208190ba14c91fb90e15ca |
completed | April 29, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69e73011e6388190a05edf137f488441 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:44 p.m.