Triple
T13694407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No Good Deed |
E328346
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | Randy Bricker |
E542303
|
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: Randy Bricker | Statement: [No Good Deed, editor, Randy Bricker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Randy Bricker Context triple: [No Good Deed, editor, Randy Bricker]
-
A.
Randy Bricker
chosen
Randy Bricker is a film editor known for his work on horror and genre films, including Texas Chainsaw 3D.
-
B.
Randy Wilson
Randy Wilson is known as the spouse of prominent American clergyman and social activist William Sloane Coffin.
-
C.
Don D. Scott
Don D. Scott is an American screenwriter best known for writing the hit comedy film "Barbershop" and its sequel.
-
D.
Jim Gilstrap
Jim Gilstrap is an American soul and R&B singer best known for his session work and for singing the male lead vocal on the theme song to the television show "Good Times."
-
E.
Tim Latta
Tim Latta is a soccer executive best known for serving as the general manager of the early Major League Soccer club Kansas City Wiz (now Sporting Kansas City).
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc8757b648190a26181efbad09a43 |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3cfae6bc8190ac6851a3fa2dfb12 |
completed | May 8, 2026, 1:31 a.m. |
Created at: April 9, 2026, 9:54 p.m.