[PDF] Top 20 Joint Distant and Direct Supervision for Relation Extraction

... State-of-the-art ACE RE, i.e. (Zhang et al., 2006; Nguyen et al., 2009), uses tree kernels applied to constituent and dependency syntactic structures, extracted from the sentences expressing the target relations. Given a ... See full document

... Neural Models for Distant Supervision. More recently, neural models have been effectively used to model textual relations (e.g., Hashimoto et al., 2013; Zeng et al., 2014; Nguyen and Grishman, 2015). ... See full document

... These methods have been shown to be effec- tive for relation extraction. However, their per- formance depends strongly on the quality of the designed features. Most existing studies have con- centrated on ... See full document

... In this paper, building on recent advances from the nonparametric Bayesian literature, we reformulate the task of relation extraction with distant super- vision, based on the adaptive variance ... See full document

... Distant supervision (DS) is an important paradigm for automatically extracting rela- ...the relation we intend to extract, and then uses these examples to au- tomatically generate the training ... See full document

... Distant supervision relation extraction is to pre- dict the relation type of entity pair under the automatically-generated training ...of relation extraction cannot sat- ... See full document

... the relation “location/location/contains” obtains a large number of 26599 sentence pairs, the relation “busi- ness/company/industry” obtains a lower number of 1529 sentence ...sentence relation ... See full document

... tions. As shown in Figure 1, of the 133 (7.3%) sentences that truly express one of these relations, only 32 (1.7%) are covered by Freebase, leaving 101 (5.5%) false negatives. Even for one of the most complete relations ... See full document

... Distant supervision, a paradigm of rela- tion extraction where training data is cre- ated by aligning facts in a database with a large unannotated corpus, is an attractive approach for training ... See full document

... many relation extraction meth- ods using neural networks with attention mecha- nism (Lin et ...a relation-aware ...to relation BornIn, the sen- tence S1 should have higher weight than S2, but ... See full document

... We extract a total number of 251917 entity pairs from the WikiTable dataset which do not exist in the NYT dataset but have at least one anchor entity pair that appear in the original NYT training data. We randomly sample ... See full document

... in distant supervision, because this is a case where data is not missing at random ...a joint model of extraction from text and the process by which propositions are observed or missing in ... See full document

... In this paper, we use the KBP corpus as test data, which includes about 1.3 million docu- ments of newswire and 0.5 million of web data. We evaluate passage retrieval algorithms on one of the most frequent relations in ... See full document

... Figure 8 shows an example of PCNNs+WN from the testing data. The entity-relation tuple is (Fort-Dix, New-Jersey, con- tains). There are 6 sentences containing the entity pair. The 4-th sentence, being the part of ... See full document

... Distant supervision (DS) for RE is based on the following assumption: (i) a sentence is connected in some way to a database of relations and (ii) such sentence contains the pair of entities partic- ipating ... See full document

... When relation extraction is performed automat- ically using machine learning approaches, this complexity results in a lack of training exam- ...is distant supervision (DS), initially proposed ... See full document

... event extraction centered around airplane crash ...that joint learning (here using the S EARN algorithm (Daum´e III, 2006)) performs better than several strong baselines, even in this complex and noisy ... See full document

... timeline extraction that uses the development data provided as distant supervision to generate noisy training data (Craven and Kumlien, 1999; Mintz et ...ing joint inference for both anchoring ... See full document

... the relation prediction of entity pairs, so we can adopt our generator as the true-positive indicator to filter the noisy distant supervision dataset be- fore relation extraction, which ... See full document

... two distant supervision models that support multi-instance learning and overlapping relations; 3) Mintz++ is a single-instance learning algorithm for distant ... See full document