Papers by Edward Newell

3 papers
Constructing a Lexicon of Relational Nouns (L18-1)

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Challenge: Existing systems for extracting relations expressed using nouns do not exist for relational noun.
Approach: They contribute a lexicon of 6,224 labeled nouns which includes 1,446 relational noun.
Outcome: The proposed classifier achieves 70.4% F1 on held out nouns among the most common 2,500 word types in Gigaword.
An Attribution Relations Corpus for Political News (L18-1)

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Challenge: Existing resources for recognizing attributions in context are limited in size and completeness.
Approach: They propose to use the largest and most complete attribution relations corpus to date . they propose to create sophisticated end-to-end solutions for attribution extraction .
Outcome: The political news attribution relations corpus 2016 is the largest and most complete attribution relations corpuse to date.
Deconstructing word embedding algorithms (2020.emnlp-main)

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Challenge: Word embeddings are reliable feature representations of words used in many NLP tasks today.
Approach: They propose to deconstruct Word2vec, GloVe and others into a common form . they propose to generalize several word embedding algorithms into . a low rank embedder framework is proposed to generalise the algorithms into one common form.
Outcome: The proposed framework can be used to make word embeddings more performant.

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