2026-09-22T02:45:59Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/101214 2023-07-11 col_2142_5131 col_2142_8888 com_2142_5130 com_2142_8887 com_2142_234

Roth, Dan Muddireddy, Pavankumar Reddy 2018-09-04T20:36:52Z 2018-09-04T20:36:52Z 2020-09-05T09:15:29Z 2018-04-24 2018-05 Named entity recognition (NER) is a natural language processing (NLP) task that involves identifying mentions (spans of text) denoting entities in a given text document and assigning them a semantic category/type from a given taxonomy. It is considered to be one of the fundamental tasks in NLP and forms the basis for higher level understanding. In this thesis, we deal with fine-grained entity type recognition, which is a variant of the classic NER task where the usual types are sub-divided into fine-grained types. We show that the current approaches, which address this problem using only local context, are insufficient to completely address the problem. We systematically identify the fundamental challenges and misconceptions that underlie the assumptions, approaches and evaluation methodologies of this task and propose improvements and alternatives. We do this by first analyzing the role of context and background knowledge in the task of fine-grained entity typing. Second, we introduce a modular architecture for fine-grained typing of entities and show that a rather simple instantiation of these modules reaches the state-of-the-art performance. Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2020-05-01 The student, Pavankumar Reddy Muddireddy, accepted the attached license on 2018-04-23 at 17:30. The student, Pavankumar Reddy Muddireddy, submitted this Thesis for approval on 2018-04-23 at 17:42. This Thesis was approved for publication on 2018-04-24 at 09:20. DSpace SAF Submission Ingestion Package generated from Vireo submission #12436 on 2018-08-31 at 17:21:20 Made available in DSpace on 2018-09-04T20:36:52Z (GMT). No. of bitstreams: 2 MUDDIREDDY-THESIS-2018.pdf: 446805 bytes, checksum: 30dc454cac28cfff02a4762ba75d774a (MD5) LICENSE.txt: 4224 bytes, checksum: b8203e25ef7f7ebfd07f9694a6abae27 (MD5) Previous issue date: 2018-04-24 Embargo set by: Seth Robbins for item 107298 Lift date: 2020-09-04T20:37:00Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system Embargo set by: Seth Robbins for item 107298 Lift date: 2020-09-04T20:42:08Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system U of I Only Restriction Lifted for Item 107298 on 2020-09-05T09:15:29Z. application/pdf http://hdl.handle.net/2142/101214 en Copyright 2018 Pavankumar Reddy Muddireddy named entity recognition NER fine-grained named entity recognition finet figer information retrieval entity typing fine-grained typing Fine-grained entity typing system - design and analysis text text Electrical & Computer Eng Electrical and Computer Engineering University of Illinois at Urbana-Champaign Thesis M.S.