Triple
T21352179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank Rossi |
E526512
|
entity |
| Predicate | primaryRelationshipInStory |
P117137
|
FINISHED |
| Object | relationship with Ruby Rossi |
—
|
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: relationship with Ruby Rossi | Statement: [Frank Rossi, primaryRelationshipInStory, relationship with Ruby Rossi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryRelationshipInStory Context triple: [Frank Rossi, primaryRelationshipInStory, relationship with Ruby Rossi]
-
A.
associatedWithPersonInStory
chosen
Indicates that one entity has a connection or involvement with a specific person within the context of a story.
-
B.
primaryInteraction
Indicates the main or most significant interaction occurring between the involved entities.
-
C.
primaryFor
Indicates that one entity serves as the main or principal option, resource, or association for another entity among possible alternatives.
-
D.
primarySeries
Indicates that one entity is the main or principal sequence, set, or collection to which another entity is related or belongs.
-
E.
relationshipCoverStory
Indicates that one relationship is being used as a cover or pretense to conceal the true nature of another relationship or situation.
- 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_69e0b51cd5cc81909ac1187971e8a8ad |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8ad33b3388190b9bc8dd5343e5a86 |
completed | April 22, 2026, 11:12 a.m. |
| PD | Predicate disambiguation | batch_69e6161feea4819091d13bb003363279 |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 5:04 p.m.