Triple
T15674385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daka Parimova |
E377399
|
entity |
| Predicate | relationshipTypeWithVincent |
P119722
|
FINISHED |
| Object | romantic partner |
—
|
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: romantic partner | Statement: [Daka Parimova, relationshipTypeWithVincent, romantic partner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithVincent Context triple: [Daka Parimova, relationshipTypeWithVincent, romantic partner]
-
A.
hasRelationshipTypeWith Vince Tyler
Indicates that an entity is connected to Vince Tyler by a specific, characterized type of relationship.
-
B.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
C.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
D.
relationshipToTony
Indicates the specific type of relationship or connection that an entity has with Tony.
-
E.
relationshipTypeWithEunice
Indicates the specific nature or category of the relationship that an entity has with Eunice.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f2c996c8190a9ebe0e92608feaa |
completed | April 16, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69deda8b36a4819081cb5708fe77ef51 |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:16 a.m.