Triple
T19252006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meet the Blacks |
E481415
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object |
Jason Gourson
Jason Gourson is a composer and music producer known for creating the musical score for the comedy horror film "Meet the Blacks."
|
E1404328
|
NE FINISHED |
How this triple was built (4 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 Gourson | Statement: [Meet the Blacks, musicBy, Jason Gourson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jason Gourson Context triple: [Meet the Blacks, musicBy, Jason Gourson]
-
A.
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.
-
B.
Jeff Gourson
Jeff Gourson is a film editor known for his work on movies such as the comedy "White Chicks."
-
C.
Josh Gorges
Josh Gorges is a Canadian former professional ice hockey defenceman best known for his NHL career with the Montreal Canadiens and Buffalo Sabres.
-
D.
Jason Geter
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.
-
E.
Jason Sehorn
Jason Sehorn is a former American football cornerback best known for his NFL career with the New York Giants in the 1990s and early 2000s.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Jason Gourson Triple: [Meet the Blacks, musicBy, Jason Gourson]
Generated description
Jason Gourson is a composer and music producer known for creating the musical score for the comedy horror film "Meet the Blacks."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jason Gourson Target entity description: Jason Gourson is a composer and music producer known for creating the musical score for the comedy horror film "Meet the Blacks."
-
A.
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.
-
B.
Jeff Gourson
Jeff Gourson is a film editor known for his work on movies such as the comedy "White Chicks."
-
C.
Josh Gorges
Josh Gorges is a Canadian former professional ice hockey defenceman best known for his NHL career with the Montreal Canadiens and Buffalo Sabres.
-
D.
Jason Geter
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.
-
E.
Jason Sehorn
Jason Sehorn is a former American football cornerback best known for his NFL career with the New York Giants in the 1990s and early 2000s.
- F. None of above. chosen
Provenance (5 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_69d8e8cd9d1081908a181d02b88b59b8 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fb30bf6c819094c44aceb544a023 |
completed | April 20, 2026, 10:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07fdb0fdb081908e803fb558158374 |
completed | May 16, 2026, 5:16 a.m. |
| NEDg | Description generation | batch_6a07fe4573a48190919a59e466b34e35 |
completed | May 16, 2026, 5:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07fede18a08190a7a7a698d7598023 |
completed | May 16, 2026, 5:21 a.m. |
Created at: April 10, 2026, 1:28 p.m.