Triple
T13240323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Good Behavior |
E315262
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Joey Kern |
E1030149
|
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: Joey Kern | Statement: [Good Behavior, starring, Joey Kern]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joey Kern Context triple: [Good Behavior, starring, Joey Kern]
-
A.
Joey Kern
chosen
Joey Kern is an American actor known for his roles in films like "Cabin Fever" and "Super Troopers," as well as various television appearances.
-
B.
Joey Luft
Joey Luft is an American television producer and occasional actor best known as the son of legendary entertainer Judy Garland and producer Sidney Luft.
-
C.
Joey Williams
Joey Williams is an American gospel musician and guitarist best known for his work with the legendary vocal group The Blind Boys of Alabama.
-
D.
Joey Newman
Joey Newman is an American composer and conductor known for his work on television scores and themes, including contributions to major sports broadcasts.
-
E.
Joey Wells
Joey Wells is a screenwriter best known for co-writing the comedy film "Night School."
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d5850ac8190849a51da39efe5be |
completed | April 10, 2026, 11:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716c6797c819090bfcc9a5b62ac1c |
completed | May 3, 2026, 9:35 a.m. |
Created at: April 9, 2026, 9:23 p.m.