Triple
T6479621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shulman |
E146154
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Mark Shulman
Mark Shulman is an American author best known for writing numerous children's books and humorous, educational titles for young readers.
|
E603619
|
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: Mark Shulman | Statement: [Shulman, hasNotableBearer, Mark Shulman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Shulman Context triple: [Shulman, hasNotableBearer, Mark Shulman]
-
A.
Dan Shulman
Dan Shulman is a Canadian sportscaster best known for his long-running play-by-play work on Major League Baseball and college basketball broadcasts for ESPN and other networks.
-
B.
Adam Shulman
Adam Shulman is an American actor and jewelry designer best known as the husband of actress Anne Hathaway.
-
C.
Luke Shapiro
Luke Shapiro is the teenage marijuana dealer and emotionally troubled protagonist of the coming-of-age film "The Wackness," set in 1990s New York City.
-
D.
Steven Baigelman
Steven Baigelman is an American screenwriter and producer known for his work on biographical and crime dramas in film and television.
-
E.
Josh Kesselman
Josh Kesselman is a film and television producer best known for his work as an executive producer on projects such as the series "The Great."
- 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: Mark Shulman Triple: [Shulman, hasNotableBearer, Mark Shulman]
Generated description
Mark Shulman is an American author best known for writing numerous children's books and humorous, educational titles for young readers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mark Shulman Target entity description: Mark Shulman is an American author best known for writing numerous children's books and humorous, educational titles for young readers.
-
A.
Dan Shulman
Dan Shulman is a Canadian sportscaster best known for his long-running play-by-play work on Major League Baseball and college basketball broadcasts for ESPN and other networks.
-
B.
Adam Shulman
Adam Shulman is an American actor and jewelry designer best known as the husband of actress Anne Hathaway.
-
C.
Luke Shapiro
Luke Shapiro is the teenage marijuana dealer and emotionally troubled protagonist of the coming-of-age film "The Wackness," set in 1990s New York City.
-
D.
Steven Baigelman
Steven Baigelman is an American screenwriter and producer known for his work on biographical and crime dramas in film and television.
-
E.
Josh Kesselman
Josh Kesselman is a film and television producer best known for his work as an executive producer on projects such as the series "The Great."
- 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_69c008fec7408190af7b146dc63d9750 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a4e764c819086828bb841f588e0 |
completed | March 22, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d50423808190817cad8601490a77 |
completed | March 27, 2026, 7:05 p.m. |
| NEDg | Description generation | batch_69c6d6732d9c8190878b54902306b128 |
completed | March 27, 2026, 7:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6d82d77388190a3022a2366a5aec7 |
completed | March 27, 2026, 7:19 p.m. |
Created at: March 22, 2026, 4:51 p.m.