Triple
T1583896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Itzhak Perlman |
E34027
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Toby Perlman
Toby Perlman is an American violinist and music educator, best known as the founder and director of the Perlman Music Program, which trains gifted young string players.
|
E179334
|
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: Toby Perlman | Statement: [Itzhak Perlman, spouse, Toby Perlman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Toby Perlman Context triple: [Itzhak Perlman, spouse, Toby Perlman]
-
A.
Ryan Roslansky
Ryan Roslansky is the CEO of LinkedIn, known for leading the professional networking platform’s product and business strategy.
-
B.
Nathan Grossman
Nathan Grossman is a Swedish documentary filmmaker best known for directing the climate activist portrait film "I Am Greta."
-
C.
Sam Zussman
Sam Zussman is a sports and media executive who serves as a top business leader for the NBA’s Brooklyn Nets organization.
-
D.
Toby Pohlen
Toby Pohlen is a member of the team at xAI, the artificial intelligence company founded by Elon Musk.
-
E.
Joshua Michael Stern
Joshua Michael Stern is an American film director and screenwriter known for helming biographical and dramatic feature films.
- 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: Toby Perlman Triple: [Itzhak Perlman, spouse, Toby Perlman]
Generated description
Toby Perlman is an American violinist and music educator, best known as the founder and director of the Perlman Music Program, which trains gifted young string players.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Toby Perlman Target entity description: Toby Perlman is an American violinist and music educator, best known as the founder and director of the Perlman Music Program, which trains gifted young string players.
-
A.
Ryan Roslansky
Ryan Roslansky is the CEO of LinkedIn, known for leading the professional networking platform’s product and business strategy.
-
B.
Nathan Grossman
Nathan Grossman is a Swedish documentary filmmaker best known for directing the climate activist portrait film "I Am Greta."
-
C.
Sam Zussman
Sam Zussman is a sports and media executive who serves as a top business leader for the NBA’s Brooklyn Nets organization.
-
D.
Toby Pohlen
Toby Pohlen is a member of the team at xAI, the artificial intelligence company founded by Elon Musk.
-
E.
Joshua Michael Stern
Joshua Michael Stern is an American film director and screenwriter known for helming biographical and dramatic feature films.
- 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_69a885fceb2c8190b47e0f7c0aefbff0 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a908f0e72c8190bb7a2a0c77379060 |
completed | March 5, 2026, 4:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad4035dd7c8190817301c0a2b0b938 |
completed | March 8, 2026, 9:24 a.m. |
| NEDg | Description generation | batch_69ad411829fc81909f9dc88b3d55d431 |
completed | March 8, 2026, 9:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad417fa778819092ebabad8bdcddd3 |
completed | March 8, 2026, 9:29 a.m. |
Created at: March 4, 2026, 7:27 p.m.