Triple
T24931346
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronit Krushka |
E618995
|
entity |
| Predicate | hasSameSexRelationshipWith |
P151129
|
FINISHED |
| Object | Esti Kuperman |
—
|
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: Esti Kuperman | Statement: [Ronit Krushka, hasSameSexRelationshipWith, Esti Kuperman]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSameSexRelationshipWith Context triple: [Ronit Krushka, hasSameSexRelationshipWith, Esti Kuperman]
-
A.
featuresSameSexRelationship
chosen
Indicates that the subject includes or portrays a romantic or sexual relationship between individuals of the same sex.
-
B.
worksInCloseRelationshipWith
Indicates a collaborative professional relationship in which two or more entities work together closely and interact frequently to achieve shared goals.
-
C.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
D.
relationshipWithMen
Indicates a relationship or interaction that specifically involves men as one of the parties.
-
E.
spouseOrLover
Indicates a romantic partnership between two entities, whether formalized as a spouse or existing as a lover.
- 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_69e2fab9edd88190b86004a78a28bc20 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f453035f508190be83a3d521723acf |
completed | May 1, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69f44d77f6e88190a4643ab2cbef567b |
completed | May 1, 2026, 6:51 a.m. |
Created at: April 18, 2026, 5:30 a.m.