Triple
T13891479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Belushi |
E333980
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Judith Belushi Pisano |
E333359
|
NE 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: Judith Belushi Pisano | Statement: [John Belushi, spouse, Judith Belushi Pisano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Judith Belushi Pisano Context triple: [John Belushi, spouse, Judith Belushi Pisano]
-
A.
Judith Belushi Pisano
chosen
Judith Belushi Pisano is an American writer, producer, and artist best known for preserving and chronicling the legacy of her late husband, comedian and actor John Belushi.
-
B.
Deanna Piatelli
Deanna Piatelli is known as the spouse of Jack Dempsey.
-
C.
Rona Lisa Peretti
Rona Lisa Peretti is a key adult character in the musical "The 25th Annual Putnam County Spelling Bee," serving as the warm yet tightly wound host and former champion of the competition.
-
D.
Judy Bluthal
Judy Bluthal is known primarily as the wife of Polish-born Australian-British actor and comedian John Bluthal.
-
E.
Judy Luciano
Judy Luciano is known for being married to American actor and comedian Don Adams, famed for his role in the television series "Get Smart."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a537d4819093c2bae2a244816a |
completed | April 14, 2026, 11:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c71a43908190bc7537f0a2379599 |
completed | May 3, 2026, 10:07 p.m. |
Created at: April 9, 2026, 10:15 p.m.