Triple
T15987699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luke and Laura wedding |
E387738
|
entity |
| Predicate | hasActor |
P1668
|
FINISHED |
| Object |
Kin Shriner
Kin Shriner is an American actor best known for his long-running role as Scott Baldwin on the soap opera "General Hospital."
|
E1187969
|
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: Kin Shriner | Statement: [Luke and Laura wedding, hasActor, Kin Shriner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kin Shriner Context triple: [Luke and Laura wedding, hasActor, Kin Shriner]
-
A.
Randy Bricker
Randy Bricker is a film editor known for his work on horror and genre films, including Texas Chainsaw 3D.
-
B.
Don D. Scott
Don D. Scott is an American screenwriter best known for writing the hit comedy film "Barbershop" and its sequel.
-
C.
Cal McVey
Cal McVey was a 19th-century American baseball player and one of the sport’s earliest professional stars, known for his versatility in the infield and outfield.
-
D.
Hugh Shelton
Hugh Shelton is a retired U.S. Army general who served as Chairman of the Joint Chiefs of Staff and played key leadership roles in major American military operations of the 1990s.
-
E.
Clint Bolick
Clint Bolick is an American lawyer, legal scholar, and Arizona Supreme Court justice known for his work on constitutional law, civil liberties, and free-market public interest litigation.
- 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: Kin Shriner Triple: [Luke and Laura wedding, hasActor, Kin Shriner]
Generated description
Kin Shriner is an American actor best known for his long-running role as Scott Baldwin on the soap opera "General Hospital."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kin Shriner Target entity description: Kin Shriner is an American actor best known for his long-running role as Scott Baldwin on the soap opera "General Hospital."
-
A.
Randy Bricker
Randy Bricker is a film editor known for his work on horror and genre films, including Texas Chainsaw 3D.
-
B.
Don D. Scott
Don D. Scott is an American screenwriter best known for writing the hit comedy film "Barbershop" and its sequel.
-
C.
Cal McVey
Cal McVey was a 19th-century American baseball player and one of the sport’s earliest professional stars, known for his versatility in the infield and outfield.
-
D.
Hugh Shelton
Hugh Shelton is a retired U.S. Army general who served as Chairman of the Joint Chiefs of Staff and played key leadership roles in major American military operations of the 1990s.
-
E.
Clint Bolick
Clint Bolick is an American lawyer, legal scholar, and Arizona Supreme Court justice known for his work on constitutional law, civil liberties, and free-market public interest litigation.
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1575993948190a05d60fc9d0c05fa |
completed | April 16, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3cfc8d08190a02abc90c889c8e1 |
completed | May 9, 2026, 11:31 p.m. |
| NEDg | Description generation | batch_69ffc4ed71648190983a0a4150c4d8c4 |
completed | May 9, 2026, 11:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffc5a5b46881908589fd1dabef5378 |
completed | May 9, 2026, 11:39 p.m. |
Created at: April 10, 2026, 4:54 a.m.