Going out on a limb: Joint Extraction of Entity Mentions and Relations without Dependency Trees
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1,025 citations
Cites background from "Going out on a limb: Joint Extracti..."
...Katiyar and Cardie [167] proposed a joint extraction framework with an attentionbased LSTM network....
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355 citations
325 citations
310 citations
Cites background or methods or result from "Going out on a limb: Joint Extracti..."
...Unlike previous work on joint models (Katiyar & Cardie, 2017), we are able to predict multiple relations considering the classes as independent and not mutually exclusive (the probabilities do not necessarily sum to 1 for different classes)....
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...1Note that another difference is that we use a CRF layer for the NER part, while Katiyar & Cardie (2017) uses a softmax and Bekoulis et al. (2017) uses a quadratic scoring layer; see further, when we discuss performance comparison results in Section 5....
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...Finally, we solve the underlying problem of the models proposed by Katiyar & Cardie (2017) and Bekoulis et al. (2017), who essentially assume classes (i.e., relations) to be mutually exclusive: we solve this by phrasing the relation extraction component as a multi-label prediction problem.1 To…...
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...We treat a relation as correct when its type and argument entities are correct, similar to Miwa & Bansal (2016) and Katiyar & Cardie (2017)....
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...Unlike the work of Katiyar & Cardie (2017), the class probabilities do not necessarily sum up to one since the classes are considered independent....
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270 citations
References
72,897 citations
"Going out on a limb: Joint Extracti..." refers methods in this paper
...RNNs (Hochreiter and Schmidhuber, 1997) have been recently applied to many sequential modeling and prediction tasks, such as machine translation (Bahdanau et al....
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33,597 citations
"Going out on a limb: Joint Extracti..." refers methods in this paper
...We regularize our network using dropout (Srivastava et al., 2014) with the drop-out rate tuned using development set....
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24,012 citations
"Going out on a limb: Joint Extracti..." refers methods in this paper
...…word embeddings 1 We ran the system made publicly available by Miwa and Bansal (2016), on ACE05 dataset for filling in the missing values and comparing our system with theirs at fine-grained level. with 300-dimensional word2vec (Mikolov et al., 2013) word embeddings trained on Google News dataset....
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...with 300-dimensional word2vec (Mikolov et al., 2013) word embeddings trained on Google News dataset....
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20,027 citations
"Going out on a limb: Joint Extracti..." refers background or methods in this paper
...RNNs (Hochreiter and Schmidhuber, 1997) have been recently applied to many sequential modeling and prediction tasks, such as machine translation (Bahdanau et al., 2015; Sutskever et al., 2014), named entity recognition (NER) (Hammerton, 2003), opinion mining (Irsoy and Cardie, 2014)....
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...Such models have been very frequently used in question-answering tasks (for recent examples, see Chen et al. (2016) and Lee et al. (2016)), machine translation (Luong et al., 2015; Bahdanau et al., 2015), and many other NLP applications....
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14,077 citations