Triple
T15199675
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Best Seller |
E363232
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object |
Ken Lerner
Ken Lerner is an American character actor known for his numerous film and television roles, often portraying nervous or officious professionals.
|
E1152213
|
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: Ken Lerner | Statement: [Best Seller, starring, Ken Lerner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ken Lerner Context triple: [Best Seller, starring, Ken Lerner]
-
A.
Mark Lerner
Mark Lerner is an American businessman best known as a principal owner of the Washington Nationals Major League Baseball team and the son of real estate magnate Ted Lerner.
-
B.
Ken Lemberger
Ken Lemberger is a film producer known for his work on the 2006 adaptation of "All the King's Men."
-
C.
Ted Lerner
Ted Lerner was an American real estate developer and principal owner of the Washington Nationals Major League Baseball team.
-
D.
George Lerner
George Lerner was an American toy inventor best known for creating the iconic Mr. Potato Head character.
-
E.
Ben L. Perry
Ben L. Perry was a screenwriter best known for his work on mid-20th-century American genre films, including the Western noir "Terror in a Texas Town."
- 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: Ken Lerner Triple: [Best Seller, starring, Ken Lerner]
Generated description
Ken Lerner is an American character actor known for his numerous film and television roles, often portraying nervous or officious professionals.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ken Lerner Target entity description: Ken Lerner is an American character actor known for his numerous film and television roles, often portraying nervous or officious professionals.
-
A.
Mark Lerner
Mark Lerner is an American businessman best known as a principal owner of the Washington Nationals Major League Baseball team and the son of real estate magnate Ted Lerner.
-
B.
Ken Lemberger
Ken Lemberger is a film producer known for his work on the 2006 adaptation of "All the King's Men."
-
C.
Ted Lerner
Ted Lerner was an American real estate developer and principal owner of the Washington Nationals Major League Baseball team.
-
D.
George Lerner
George Lerner was an American toy inventor best known for creating the iconic Mr. Potato Head character.
-
E.
Ben L. Perry
Ben L. Perry was a screenwriter best known for his work on mid-20th-century American genre films, including the Western noir "Terror in a Texas Town."
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b476208190a5119710c518bb1f |
completed | April 15, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff01dc23d081908ad6985bae5741ce |
completed | May 9, 2026, 9:43 a.m. |
| NEDg | Description generation | batch_69ff02fa44dc8190b536101171d907c3 |
completed | May 9, 2026, 9:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff04844a8c8190868a3bb5c363f1a3 |
completed | May 9, 2026, 9:55 a.m. |
Created at: April 10, 2026, 3:10 a.m.