Triple
T14880280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cass Silenski |
E349981
|
entity |
| Predicate | relationshipTypeWithVivaldoMoore |
P116177
|
FINISHED |
| Object | extramarital 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: extramarital affair | Statement: [Cass Silenski, relationshipTypeWithVivaldoMoore, extramarital affair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithVivaldoMoore Context triple: [Cass Silenski, relationshipTypeWithVivaldoMoore, extramarital affair]
-
A.
relationshipToAnnaMoore
Indicates the specific familial, social, or professional relationship that one entity has to Anna Moore.
-
B.
relationshipToAntonioVillalta
Indicates the nature of the relationship or connection that an entity has to Antonio Villalta.
-
C.
worksInCloseRelationshipWith
Indicates a collaborative professional relationship in which two or more entities work together closely and interact frequently to achieve shared goals.
-
D.
relationshipToPavelVlasov
Indicates the nature or type of relationship an entity has with Pavel Vlasov.
-
E.
relationshipTypeWithEvePolastri
Indicates the specific nature or category of relationship that an entity has with Eve Polastri.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5e622388190b2bf91cd10b9821d |
completed | April 15, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69de8c1a2bcc81908f914e2e2ced65eb |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4c76e481909c0aa8d1a978e8d5 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:55 a.m.