Triple
T11376850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Livia Soprano |
E269490
|
entity |
| Predicate | relationshipWithBarbaraSopranoGiglione |
P98978
|
FINISHED |
| Object | distant |
—
|
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: distant | Statement: [Livia Soprano, relationshipWithBarbaraSopranoGiglione, distant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipWithBarbaraSopranoGiglione Context triple: [Livia Soprano, relationshipWithBarbaraSopranoGiglione, distant]
-
A.
relationshipToTinaBordereau
Indicates the specific type of personal or professional relationship an entity has with Tina Bordereau.
-
B.
relationshipStatusWithElaineBenes
Indicates the nature or current state of an entity’s interpersonal or romantic relationship with Elaine Benes.
-
C.
relationshipToMargoChanning
Indicates the nature or type of relationship an entity has with Margo Channing.
-
D.
relationshipToGabeGoodman
Indicates the specific type of personal or social relationship an entity has with Gabe Goodman.
-
E.
relationshipToDianaGoodman
Indicates a specified type of relationship or connection that an entity has to Diana Goodman.
- 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_69d6aacca1048190b39dbbc2174616fa |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d800160a1c81909d115bf89fe54a49 |
completed | April 9, 2026, 7:37 p.m. |
| PD | Predicate disambiguation | batch_69d7e7022d508190996f9be0847c2b41 |
completed | April 9, 2026, 5:50 p.m. |
| PDg | Predicate description generation | batch_69d80010712c819089ea2e31e664abe1 |
completed | April 9, 2026, 7:37 p.m. |
Created at: April 8, 2026, 9:33 p.m.