[PDF] Top 20 An Improved Neural Baseline for Temporal Relation Extraction

... Determining temporal relations ...Consequently, neural approaches have not been widely used on it, or showed only moderate ...new neural system that achieves about 10% absolute improvement in ... See full document

... Relation extraction, the task of extracting seman- tic relations between named entities mentioned in text, has become a key research topic in natu- ral language processing (NLP) with a variety of practical ... See full document

... supervised relation extraction has been widely used to find novel rela- tional facts from plain ...the relation between a pair of two target entities, existing methods solely rely on those direct ... See full document

... Fig. 4 shows the precision/recall curves for each method. We can observe that: (1) CNN/PCNN+ATT significantly outperforms all feature-based methods over the entire range of re- call. When the recall is greater than 0.1, ... See full document

... tive container relations and document creation time relations. Herein, we focus on the second part of the challenge, temporal relation extrac- tion and more specifically the narrative container relations. ... See full document

... Manirupa Das, Eric Fosler-Lussier, Simon Lin, Soheil Moosavinasab, David Chen, Steve Rust, Yungui Huang and Rajiv Ramnath . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ... See full document

... on temporal rela- tion extraction ( § 2) and then present our frame- work and data collection methodology ...largest temporal relation dataset to date, covering all of the Univer- sal ... See full document

... now, relation extraction systems have made extensive use of features generated by linguistic analysis ...of relation detection and ...tional neural network for relation ... See full document

... the baseline, shows that in the cases that supervised methods can beat the baseline method, our weakly supervised method can also work better than the baseline or close to ... See full document

... first baseline is the best performing system of the Clinical TempEval 2016 on the DCTR task (Khalifa et ...TLINK baseline is the latest version of the cTAKES Temporal system (Lin et ...recently ... See full document

... study relation extraction for knowledge base (KB) ...the extraction itself and rely on Named Entity Disambiguation (NED) to map triples into the KB ...cause extraction errors that affect the ... See full document

... the relation of one pair does not affect the classification results for other ...same neural network, rather than by three separately trained models; (2) the neighbor- ing words (a flat context) of entity ... See full document

... encoding relation argu- ment positions and show that CNNs and LSTMs can be successfully used for temporal relation ex- traction, establishing a new state-of-the-art ...a neural model can be ... See full document

... events temporal rela- ...recurrent neural networks (RNNs) to learn long-term ...employing neural network models for event tem- poral relation extraction (Tourille et ... See full document

... of neural network models, we would like to leverage the emerging attention ...i.e. temporal relation indicators for each relation instance of a ... See full document

... new deep learning world has called for minimal- istic pre-processing as input to powerful learners. We propose a new direction to combine the best of both worlds – infusing some knowledge into the learner input. For CNN ... See full document

... THYME system. While recall reached its peak with the self-trained SVM, the precision trade-off was disastrous and F1 suffers dramatically. Our in- terpretation of this result is that the SVM is simply adjusting its class ... See full document

... The temporal relations used by the THYME project rely on Allen (1990) in- terval algebra, a precise way to express time pe- riods using clear start and end ... See full document

... for relation extraction, it shows several many new research directions for the ...each relation with a group of annotators and use semi-supervised training to expand the rationale ... See full document

... The rest of the paper is organized as follows. In Section 2, we introduce the kernel-based machine learning algorithms and their application in nat- ural language processing problems. In Section 3, we formalize the ... See full document