Triple

T2908928
Position Surface form Disambiguated ID Type / Status
Subject Bear Stearns E63634 entity
Predicate ceo P2568 FINISHED
Object Alan Schwartz
Alan Schwartz is an American investment banker best known for serving as the last chief executive officer of Bear Stearns during its 2008 collapse and sale to JPMorgan Chase.
E340018 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: Alan Schwartz | Statement: [Bear Stearns, ceo, Alan Schwartz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alan Schwartz
Context triple: [Bear Stearns, ceo, Alan Schwartz]
  • A. Daniel Scharf
    Daniel Scharf is a film producer best known for his work on the influential 1992 Australian drama "Romper Stomper."
  • B. Philip Brownstein
    Philip Brownstein was a professional basketball coach best known for leading the early NBA-era Chicago Stags franchise.
  • C. Allen Shapiro
    Allen Shapiro is an American entertainment executive and film producer known for his work on projects such as the Western film "The Quick and the Dead."
  • D. Don Katz
    Don Katz is an American entrepreneur and author best known as the founder of the audiobook and spoken-word entertainment company Audible.
  • E. Steven Baigelman
    Steven Baigelman is an American screenwriter and producer known for his work on biographical and crime dramas in film and television.
  • 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: Alan Schwartz
Triple: [Bear Stearns, ceo, Alan Schwartz]
Generated description
Alan Schwartz is an American investment banker best known for serving as the last chief executive officer of Bear Stearns during its 2008 collapse and sale to JPMorgan Chase.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Alan Schwartz
Target entity description: Alan Schwartz is an American investment banker best known for serving as the last chief executive officer of Bear Stearns during its 2008 collapse and sale to JPMorgan Chase.
  • A. Michael Saltzman
    Michael Saltzman is a screenwriter best known for co-writing the 2006 reboot of "The Pink Panther" starring Steve Martin.
  • B. Daniel Scharf
    Daniel Scharf is a film producer best known for his work on the influential 1992 Australian drama "Romper Stomper."
  • C. Philip Brownstein
    Philip Brownstein was a professional basketball coach best known for leading the early NBA-era Chicago Stags franchise.
  • D. Allen Shapiro
    Allen Shapiro is an American entertainment executive and film producer known for his work on projects such as the Western film "The Quick and the Dead."
  • E. Don Katz
    Don Katz is an American entrepreneur and author best known as the founder of the audiobook and spoken-word entertainment company Audible.
  • 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_69ab4c44ab448190b9411324e8a1fc1d completed March 6, 2026, 9:51 p.m.
NER Named-entity recognition batch_69abe0d329c88190b6fcaef0be1799eb completed March 7, 2026, 8:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69b276cc19b48190a952015c9e501dd6 completed March 12, 2026, 8:18 a.m.
NEDg Description generation batch_69b277a9ab548190a8b9822db2db3d0d completed March 12, 2026, 8:22 a.m.
NED2 Entity disambiguation (via description) batch_69b27b88c9648190a4a8271452d8ed3e completed March 12, 2026, 8:38 a.m.
Created at: March 6, 2026, 10:11 p.m.