Triple
T12993835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ya Got Trouble |
E321980
|
entity |
| Predicate | performedBy |
P1363
|
FINISHED |
| Object | Craig Bierko |
E71819
|
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: Craig Bierko | Statement: [Ya Got Trouble, performedBy, Craig Bierko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Craig Bierko Context triple: [Ya Got Trouble, performedBy, Craig Bierko]
-
A.
Craig Bierko
chosen
Craig Bierko is an American actor known for his work in film, television, and theater, often playing charismatic or villainous roles.
-
B.
Justin Raisen
Justin Raisen is an American record producer and songwriter known for his work with a wide range of indie, pop, and alternative artists.
-
C.
Mike Kellin
Mike Kellin was an American character actor known for his prolific work in film, television, and theater from the 1950s through the 1970s.
-
D.
Matthew York
Matthew York is the son of American actor Dick York, best known for his role as the original Darrin Stephens on the television series "Bewitched."
-
E.
Mike Krieger
Mike Krieger is a Brazilian-American entrepreneur and software engineer best known as the co-founder and former CTO of the photo-sharing social media platform Instagram.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e7877f481908a03f1077600e58a |
completed | April 10, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6f5c2df08819086d9a9107b0a6935 |
completed | May 3, 2026, 7:14 a.m. |
Created at: April 9, 2026, 8:44 p.m.