Supervised Noun Phrase Coreference Research: The First Fifteen Years

By Vincent Ng. 2010

301 citations recorded by the source corpus.

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Citations in the corpus

Toward Gender-Inclusive Coreference Resolution (2019, methodology): “This confirms the findings of Rudinger et al. (2018) and Zhao et al.”
End-to-end Neural Coreference Resolution (2017, background): “Machine learning methods have a long history in coreference resolution (see Ng (2010) for a detailed survey).”
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF (2016, background): “…(Nivre and Scholz, 2004; McDonald et al., 2005; Koo and Collins, 2010; Ma and Zhao, 2012a; Ma and Zhao, 2012b; Chen and Manning, 2014; Ma and Hovy, 2015) and entity coreference resolution (Ng, 2010; Ma et al., 2016), are becoming more sophisticated, in part because of utilizing output information…”
Using Coreference Links to Improve Spanish-to-English Machine Translation (2017, background): “Despite the numerous coreference and anaphora resolution systems designed in the past decades (Mitkov, 2002; Ng, 2010), the interest in using them to improve pronoun translation has only recently emerged (Le Nagard and Koehn, 2010; Hardmeier and Federico, 2010; Guillou, 2012).”
Syntactic Scaffolds for Semantic Structures (2018, methodology): “5 are due to Yang and Mitchell (2017). In their sequential model (seq), they treat argument identification as a sequence-labeling problem using a deep bidirectional LSTM with a CRF layer.”
A Joint Model for Entity Analysis: Coreference, Typing, and Linking (2014, background): “The ﬁrst is coreference resolution (Soon et al., 2001; Ng, 2010; Pradhan et al., 2011), which identiﬁes clusters of mentions in a document referring to the same entity.”
Stack-Pointer Networks for Dependency Parsing (2018, background): “A wide range of NLP applications, such as coreference resolution (Ng, 2010; Durrett and Klein, 2013; Ma et al., 2016), sentiment analysis (Tai et al.”
Broad-coverage CCG Semantic Parsing with AMR (2015, methodology): “To represent such dependencies while maintaining a relatively compact grammar, we follow Steedman’s (2011) use of generalized Skolem terms, a mechanism to allow global references in lambda calculus.”
CoNLL-2011 Shared Task: Modeling Unrestricted Coreference in OntoNotes (2011, background): “A better idea of the progress in the field can be obtained by reading recent survey articles (Ng, 2010) and tutorials (Ponzetto and Poesio, 2009) dedicated to this subject.”
Dynamic Knowledge-Base Alignment for Coreference Resolution (2013, methodology): “These results use true mentions provided in the dataset, since, as suggested by Ng (2010), coreference resolvers that use different mention detectors (extraction from parse tree, detector trained from gold boundaries, etc.”
Coreference Semantics from Web Features (2012, background): “It is well known (Recasens and Hovy, 2010; Ng, 2010; Kobdani et al., 2011) that MUC is biased towards large clusters (chains) whereas B 3 is biased towards singleton clusters.”
Learning Structured Perceptrons for Coreference Resolution with Latent Antecedents and Non-local Features (2014, background): “, (Ng, 2010)).”
Combing Context and Commonsense Knowledge Through Neural Networks for Solving Winograd Schema Problems (2016, methodology): “The DNN model works as a mention pair classifier for judging whether two mentions are coreferent or not, which is a widely used technology in the coreference resolution community (Ng 2010).”
Active Learning for Coreference Resolution (2012, background): “One can also interpret these results to inspire further work, first by noting that all of the selection techniques attempt to build on the instance selection metrics. While our document selection metrics were more sophisticated than simply taking the nbest instances, Settles (2010) notes that some s”
Commonsense Knowledge Enhanced Embeddings for Solving Pronoun Disambiguation Problems in Winograd Schema Challenge (2016, methodology): “The DNN model works as a mention pair classifier for judging whether two mentions are coreferent or not, which is a widely used technology in the coreference resolution community [27].”
Where’s My Head? Definition, Data Set, and Models for Numeric Fused-Head Identification and Resolution (2019, methodology): “The R EFERENCE case requires selecting the most adequate token over the text, suggesting a similar formulation to coreference resolution (Ng, 2010; Lee et al., 2018) and implicit arguments identiﬁcation (Gerber and Chai, 2012; Moor et al., 2013).”