Dan Jurafsky
E857263
Dan Jurafsky is a prominent computational linguist and professor known for his influential work in natural language processing and co-authoring the widely used textbook "Speech and Language Processing."
All labels observed (1)
| Label | Occurrences |
|---|---|
| Dan Jurafsky canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T10344868 — 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: Dan Jurafsky Context triple: [Nathaniel Chambers, coAuthorWith, Dan Jurafsky]
-
A.
Christopher Manning
Christopher Manning is a prominent computer scientist and linguist best known for his pioneering work in natural language processing and deep learning, and for co-leading the Stanford NLP Group.
-
B.
Mark Liberman
Mark Liberman is an American linguist known for his work in phonetics, corpus linguistics, and for co-founding the influential Language Log blog.
-
C.
Michael N. Marcus
Michael N. Marcus is a screenwriter best known for his work on the 1966 Western film "Duel at Diablo."
-
D.
Michael Kenstowicz
Michael Kenstowicz is an American linguist and phonologist known for his influential work on generative phonology and for co-authoring widely used textbooks in the field.
-
E.
David Resnik
David Resnik is an American bioethicist known for his work on research ethics, scientific integrity, and the ethical implications of environmental and public health policy.
- 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: Dan Jurafsky Target entity description: Dan Jurafsky is a prominent computational linguist and professor known for his influential work in natural language processing and co-authoring the widely used textbook "Speech and Language Processing."
-
A.
Christopher Manning
Christopher Manning is a prominent computer scientist and linguist best known for his pioneering work in natural language processing and deep learning, and for co-leading the Stanford NLP Group.
-
B.
Mark Liberman
Mark Liberman is an American linguist known for his work in phonetics, corpus linguistics, and for co-founding the influential Language Log blog.
-
C.
Michael N. Marcus
Michael N. Marcus is a screenwriter best known for his work on the 1966 Western film "Duel at Diablo."
-
D.
Michael Kenstowicz
Michael Kenstowicz is an American linguist and phonologist known for his influential work on generative phonology and for co-authoring widely used textbooks in the field.
-
E.
David Resnik
David Resnik is an American bioethicist known for his work on research ethics, scientific integrity, and the ethical implications of environmental and public health policy.
- F. None of above. chosen
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
computational linguist
ⓘ
human ⓘ textbook author ⓘ university professor ⓘ |
| almaMater | University of California, Berkeley NERFINISHED ⓘ |
| awardReceived |
ACL Fellowship
NERFINISHED
ⓘ
MacArthur Fellowship NERFINISHED ⓘ |
| coAuthorOf | "Speech and Language Processing" NERFINISHED ⓘ |
| coAuthorWith | James H. Martin NERFINISHED ⓘ |
| countryOfCitizenship | United States of America ⓘ |
| degree | PhD in linguistics ⓘ |
| educatedAt | University of California, Berkeley ⓘ |
| employer | Stanford University ⓘ |
| field |
computational linguistics
ⓘ
computer science ⓘ linguistics ⓘ natural language processing ⓘ psycholinguistics ⓘ speech processing ⓘ |
| fieldOfStudy | linguistics ⓘ |
| hasAcademicAdvisor | Charles J. Fillmore NERFINISHED ⓘ |
| hasResearchInterest |
computational pragmatics
ⓘ
dialog systems ⓘ language and food ⓘ sentiment analysis ⓘ speech recognition ⓘ statistical natural language processing ⓘ |
| hasTaughtAt | University of Colorado Boulder NERFINISHED ⓘ |
| hasWrittenOn |
applications of NLP in industry
ⓘ
language and cognition ⓘ language and social interaction ⓘ |
| knownFor |
computational linguistics
ⓘ
natural language processing ⓘ speech and language processing research ⓘ textbook "Speech and Language Processing" NERFINISHED ⓘ |
| memberOf |
Association for Computational Linguistics
NERFINISHED
ⓘ
Linguistic Society of America NERFINISHED ⓘ |
| name | Dan Jurafsky NERFINISHED ⓘ |
| nationality | American ⓘ |
| notableWork |
"Speech and Language Processing"
NERFINISHED
ⓘ
"The Language of Food" NERFINISHED ⓘ |
| occupation |
author
ⓘ
computational linguist ⓘ professor ⓘ researcher ⓘ |
| position |
Professor of Computer Science
ⓘ
Professor of Linguistics ⓘ |
| previousEmployer | University of Colorado Boulder NERFINISHED ⓘ |
| workInstitution | Stanford University NERFINISHED ⓘ |
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: Dan Jurafsky Description of subject: Dan Jurafsky is a prominent computational linguist and professor known for his influential work in natural language processing and co-authoring the widely used textbook "Speech and Language Processing."
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.