Triple
T19553546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paper Trail |
E489251
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Jason Geter |
—
|
NE NERFINISHED |
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: Jason Geter | Statement: [Paper Trail, executiveProducer, Jason Geter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jason Geter Context triple: [Paper Trail, executiveProducer, Jason Geter]
-
A.
Jason Geter
chosen
Jason Geter is an American music executive and entrepreneur best known for managing rapper T.I. and helping build the Grand Hustle brand in hip-hop.
-
B.
Jason Gesser
Jason Gesser is a former American football quarterback best known for his standout college career at Washington State University and subsequent roles as a coach and sports analyst.
-
C.
Jason Gourson
Jason Gourson is a composer and music producer known for creating the musical score for the comedy horror film "Meet the Blacks."
-
D.
Kyle Scheible
Kyle Scheible is the aloof, rebellious musician and love interest in the coming-of-age film "Lady Bird."
-
E.
Kyle Rote
Kyle Rote was a former New York Giants star running back and wide receiver who became a prominent American sportscaster and television commentator.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63d315c68819087402802d624a8c9 |
completed | April 20, 2026, 2:50 p.m. |
Created at: April 10, 2026, 1:41 p.m.