Jessica Gelman
E868869
Jessica Gelman is a prominent sports analytics executive and entrepreneur best known for co-founding and leading the influential MIT Sloan Sports Analytics Conference.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Jessica Gelman canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T10219648 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
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.
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
Statements (45)
| Predicate | Object |
|---|---|
| instanceOf |
person
ⓘ
sports analytics leader ⓘ sports executive ⓘ |
| activeSince | early 2000s ⓘ |
| advocatesFor |
data-driven decision making in sports organizations
ⓘ
greater representation of women in sports analytics ⓘ |
| almaMater | Harvard University ⓘ |
| areaOfInfluence |
North American professional sports leagues
ⓘ
linked to:
North American professional sports
sports technology and innovation ⓘ |
| awardReceived | Leaders in Sports U.S. Sports Business Award (group recognition via KAGR/Patriots-related work) ⓘ |
| basedIn | Massachusetts ⓘ |
| boardMembership |
Harvard Varsity Club (board)
ⓘ
Sports Innovation Lab (advisory or board role) ⓘ |
| coFounderOf | MIT Sloan Sports Analytics Conference ⓘ |
| conferenceOrganizerOf | MIT Sloan Sports Analytics Conference ⓘ |
| degree | MBA ⓘ |
| educatedAt |
Harvard Business School
ⓘ
Harvard College ⓘ
linked to:
Harvard University
|
| employer |
Kraft Analytics Group
ⓘ
Kraft Group ⓘ |
| fieldOfWork |
data-driven decision making in sports
ⓘ
sports analytics ⓘ |
| focusesOn |
business operations analytics for sports organizations
ⓘ
fan engagement analytics ⓘ ticketing and revenue optimization in sports ⓘ |
| gender | female ⓘ |
| hasNotableCollaborationWith | MIT Sloan School of Management ⓘ |
| hasRole | co-chair of MIT Sloan Sports Analytics Conference ⓘ |
| influenced | adoption of analytics in professional sports teams ⓘ |
| knownFor |
MIT Sloan Sports Analytics Conference
ⓘ
advancing use of data science in front-office sports decisions ⓘ promoting diversity and inclusion in sports analytics ⓘ |
| memberOf | sports analytics community ⓘ |
| nationality | American ⓘ |
| notableAchievement | helping grow MIT Sloan Sports Analytics Conference into a leading global sports analytics event ⓘ |
| notableWork | development of sports analytics applications for professional teams ⓘ |
| occupation |
conference organizer
ⓘ
data strategy executive ⓘ sports industry consultant ⓘ |
| role | CEO of Kraft Analytics Group ⓘ |
| speaksAt | sports analytics conferences ⓘ |
| sportPlayed |
basketball
ⓘ
soccer ⓘ |
| worksIn |
sports analytics industry
ⓘ
sports business ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Jessica Gelman Description of subject: Jessica Gelman is a prominent sports analytics executive and entrepreneur best known for co-founding and leading the influential MIT Sloan Sports Analytics Conference.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.