Triple

T10219648
Position Surface form Disambiguated ID Type / Status
Subject MIT Sloan Sports Analytics Conference E242539 entity
Predicate foundedBy P104 FINISHED
Object Jessica Gelman
Jessica Gelman is a prominent sports analytics executive and entrepreneur best known for co-founding and leading the influential MIT Sloan Sports Analytics Conference.
E868869 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: Jessica Gelman | Statement: [MIT Sloan Sports Analytics Conference, foundedBy, Jessica Gelman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jessica Gelman
Context triple: [MIT Sloan Sports Analytics Conference, foundedBy, Jessica Gelman]
  • A. Judith Gellman
    Judith Gellman is a costume designer best known for her work on the 1995 film adaptation of "A Little Princess."
  • B. Rachel Leibowitz
    Rachel Leibowitz is a person notable enough to be specifically cited as a bearer of the surname Leibowitz.
  • C. Janet Margolin
    Janet Margolin was an American film and television actress best known for her roles in movies such as "David and Lisa" and Woody Allen's "Annie Hall."
  • D. Gail Berman
    Gail Berman is an American television and film producer and media executive known for her influential roles at major studios and for producing high-profile projects across network TV and Hollywood.
  • E. Liz Gorinsky
    Liz Gorinsky is an acclaimed science fiction and fantasy editor known for her influential work at Tor Books and for winning major genre awards.
  • 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: Jessica Gelman
Triple: [MIT Sloan Sports Analytics Conference, foundedBy, Jessica Gelman]
Generated description
Jessica Gelman is a prominent sports analytics executive and entrepreneur best known for co-founding and leading the influential MIT Sloan Sports Analytics Conference.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jessica Gelman
Target entity description: Jessica Gelman is a prominent sports analytics executive and entrepreneur best known for co-founding and leading the influential MIT Sloan Sports Analytics Conference.
  • A. Judith Gellman
    Judith Gellman is a costume designer best known for her work on the 1995 film adaptation of "A Little Princess."
  • B. Rachel Leibowitz
    Rachel Leibowitz is a person notable enough to be specifically cited as a bearer of the surname Leibowitz.
  • C. Janet Margolin
    Janet Margolin was an American film and television actress best known for her roles in movies such as "David and Lisa" and Woody Allen's "Annie Hall."
  • D. Gail Berman
    Gail Berman is an American television and film producer and media executive known for her influential roles at major studios and for producing high-profile projects across network TV and Hollywood.
  • E. Liz Gorinsky
    Liz Gorinsky is an acclaimed science fiction and fantasy editor known for her influential work at Tor Books and for winning major genre awards.
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d3aa715a3c8190a9ccee7bcece0346 completed April 6, 2026, 12:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69d90d54c32c8190b175a30c7c905cd2 completed April 10, 2026, 2:46 p.m.
NEDg Description generation batch_69d9107c75108190994939ab46aa642f completed April 10, 2026, 3 p.m.
NED2 Entity disambiguation (via description) batch_69d9154c922c81909991f87f89c083cd completed April 10, 2026, 3:20 p.m.
Created at: April 6, 2026, 11:08 a.m.