7,620 research outputs found
Dialogical Skirmishes
No full textTan was guest editor for 'And Now China?', a special print edition of the Ctrl+P journal, which critically responded to the celebratory rhetoric’s of ‘China Now’ and other celebratory markers of China's global ascent in 2008. As well as the introductory article 'Dialogical Skirmishes', Tan also interviewed Hans Ulrich Obrist
Replication Data for: Entity-Based Evaluation of Political Bias in Automatic Summarization
No full textData for the EMNLP 2023 Findings paper "Entity-Based Evaluation of Political Bias in Automatic Summarization" by Karen Zhou and Chenhao Tan.
See https://github.com/ChicagoHAI/entity-based-political-bias for additional details about the dataset
Evidence for erbium-erbium energy migration in erbium(III) bis(perfluoro-p-tolyl)phosphinate
No full textCopyright 2008 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. This article appeared in Applied Physics Letters 92, 103303 (2008) and may be found at
Response letter from Hessel, Lee, Mimno and Tan.
No full textAuthors of all cited works were solicited for opportunities to respond to our findings—Jack Hessel, Lillian Lee, David Mimno, and Chenhao Tan jointly have provided a response. (PDF)</p
Free thinking - running
No full textWe've been running for two million years give or take. Shahidha Bari and Laurence Scott explore contemporary running as solitary inspiration and communal activity with the Geographer and 1999 Scottish Hill Running Champion, Hayden Lorimer, the artists Kai Syng Tan and Angus Farquhar, and the literary scholar and bare-foot artiste, Vybarr Cregan-Reid. Conversation ranges from feeling empowered on city streets to teaming up with the wind to the horrid history of the treadmill and explore whether Running deserves better representation in the arts. Guests: Vybarr Cregan-Reid - author of Footnotes How Running Makes Us Human Angus Farquhar, Creative Director of NVA Public Art, author of a blog 'The Grim Runner' Hayden Lorimer Running Geographer Kai Syng Tan, Artist and curator of a biennial festival Run Run Run Producer: Jacqueline Smith
HAIL HYDRA: Named Entity Resolution, Extraction, and Linking of Lexically Similar Names
No full textWords, words, words (Hamlet 2.2 18)
Characters and ideas in text are represented by names. A casual reader would have no trouble understanding that a passing reference to Mr. Holmes, Mr. Sherlock Holmes, Sherlock Holmes, and Holmes all trace back to the world’s most famous detective. Names are often shortened or rearranged with common abbreviation or elaborate titles. Each version of a character’s name can be understood as a single head on a multi-headed hydra, all tracing back to the same body. Raw text analysis requires more literary context about how English is structured and how words in a sentence interact to generate the most accurate named entities possible. Many intelligent-dependency parsers and natural language processing systems study text without accounting for how dynamic language can be. This thesis considers the entire body of a piece of literature to identify and relate entities within the same text, regardless of the fluid nature of the exact reference to an entity in literature. Once an entity has been identified, lexically similar names, which refer to the same character, can be linked together to form a global named entity that represents all forms of the named entity referenced in the text. By utilizing raw text as opposed to labeled corpus, this thesis will generate named entities from the text
HAIL HYDRA: Named Entity Resolution, Extraction, and Linking of Lexically Similar Names
No full textWords, words, words (Hamlet 2.2 18)
Characters and ideas in text are represented by names. A casual reader would have no trouble understanding that a passing reference to Mr. Holmes, Mr. Sherlock Holmes, Sherlock Holmes, and Holmes all trace back to the world’s most famous detective. Names are often shortened or rearranged with common abbreviation or elaborate titles. Each version of a character’s name can be understood as a single head on a multi-headed hydra, all tracing back to the same body. Raw text analysis requires more literary context about how English is structured and how words in a sentence interact to generate the most accurate named entities possible. Many intelligent-dependency parsers and natural language processing systems study text without accounting for how dynamic language can be. This thesis considers the entire body of a piece of literature to identify and relate entities within the same text, regardless of the fluid nature of the exact reference to an entity in literature. Once an entity has been identified, lexically similar names, which refer to the same character, can be linked together to form a global named entity that represents all forms of the named entity referenced in the text. By utilizing raw text as opposed to labeled corpus, this thesis will generate named entities from the text
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