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Temporal Reasoning on Implicit Events from Distant Supervision
[article]
2021
arXiv
pre-print
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To address this, we propose a neuro-symbolic temporal reasoning model, SYMTIME, which exploits distant supervision signals from large-scale text and uses temporal rules to combine start times and durations ...
This introduces a new challenge in temporal reasoning research, where prior work has focused on explicitly mentioned events. ...
In summary, we make the following 3 contributions: (1) a temporal relation dataset TRACIE focusing on implicit events ( §3); (2) a distant supervision process for temporal understanding of implicit events ...
arXiv:2010.12753v2
fatcat:xyzyr2quljfolcs7gyvzeodnjy
Temporal Reasoning on Implicit Events from Distant Supervision
2021
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
unpublished
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To address this, we propose a neuro-symbolic temporal reasoning model, SYMTIME, which exploits distant supervision signals from largescale text and uses temporal rules to combine start times and durations ...
This introduces a new challenge in temporal reasoning research, where prior work has focused on explicitly mentioned events. ...
In summary, we make the following 3 contributions: (1) a temporal relation dataset TRACIE focusing on implicit events ( §3); (2) a distant supervision process for temporal understanding of implicit events ...
doi:10.18653/v1/2021.naacl-main.107
fatcat:y7qativf7zc5pdrvawtnbteuqa
CUNY BLENDER TAC-KBP2011 Temporal Slot Filling System Description
2011
Text Analysis Conference
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In order to provide enough training data for these classifiers we used a distant supervision approach to automatically generate a large amount of training instances from the Web. ...
We implemented a "structured" and a "flat" approach to the classification of temporal expressions. ...
Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on. ...
dblp:conf/tac/ArtilesLCTJ11
fatcat:enylabxqvbbhpagyq3jv7fl4vy
Effective Distant Supervision for Temporal Relation Extraction
[article]
2021
arXiv
pre-print
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We scrape and automatically label event pairs where the temporal relations are made explicit in text, then mask out those explicit cues, forcing a model trained on this data to learn other signals. ...
We present a method of automatically collecting distantly-supervised examples of temporal relations. ...
We present event-label tuples in Appendix D.
MATRES Test
Related Work There is little direct prior work on using this kind of distant supervision for temporal relation extraction. ...
arXiv:2010.12755v2
fatcat:omkd67k4kzgtpokljx2q6lki7y
Paragraph-level Commonsense Transformers with Recurrent Memory
[article]
2021
arXiv
pre-print
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2020 pre-print arXiv:2010.01486v1 fatcat:bjpkdxpj7vh23oueyuwlurnlh4
However, COMET was trained on commonsense inferences of short phrases, and is therefore discourse-agnostic. ...
PARA-COMET captures both semantic knowledge pertaining to prior world knowledge, and episodic knowledge involving how current events relate to prior and future events in a narrative. ...
distant supervision. ...
arXiv:2010.01486v2
fatcat:24db6xcsnffu7cnghfizyzxmce
UNED Slot Filling and Temporal Slot Filling systems at TAC KBP 2013: System description
2013
Text Analysis Conference
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This is realized using distant supervision to match temporal information from a knowledge base and textual sources. Evidence is then aggregated into an imprecise temporal anchoring interval. ...
For the Temporal Slot Filling task, our approach is based on learning the temporal link between relation mentions and previously identified contextual temporal expressions. ...
scope of training examples to sentences, although co-reference allows to gather information from different parts of the documents; (4) in the Temporal Slot Filling task, we have integrated distant supervision ...
dblp:conf/tac/GarridoPC13
fatcat:2u4wwlunevha3p477q6rmgshgu
Extracting event and their relations from texts: A survey on recent research progress and challenges
2020
AI Open
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In event relation extraction, we focus on the extraction approaches for three typical event relation types, including coreference, causal and temporal relations, respectively. ...
How to identify events from texts, extract their arguments, even analyze the relations between different events are important for many applications. ...
Distant supervised data generation Works on distant supervised data generation aim to generate largescale labeled data by distant supervision automatically. ...
doi:10.1016/j.aiopen.2021.02.004
fatcat:qxbcmk55vzcb5nznhgfgwrbe4u
SemEval-2015 Task 5: QA TempEval - Evaluating Temporal Information Understanding with Question Answering
2015
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)
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Features that helped achieve better results are event coreference and a time expression reasoner. ...
Evaluation results show that the best automated TimeML annotations reach over 30% recall on questions with 'yes' answer and about 50% on easier questions with 'no' answers. ...
Acknowledgments We want to thank participant Paramita Mirza for her collaboration on reviewing and correcting the test data, and also Marc Verhagen and Roser Sauri for their help on approximating the time-cost ...
doi:10.18653/v1/s15-2134
dblp:conf/semeval/LlorensCUMAP15
fatcat:udyco4aefbe5xbmd2eamzd5mmq
Which Semantics for Requirements Engineering: From Shallow to Deep
2018
Requirements Engineering: Foundation for Software Quality
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future generation of natural language processing systems needs a deep semantics, that is a representation of the content independent of the surface description, which represents hidden casual, spatial, temporal ...
of system analysis improved by hand); use this with a suitable fitness function [Kra17] to improve large scale testing of the system; improve the system itself by deploying genetic algorithms based on ...
More importantly from the point of view of discourse analysis, such basic units are also positioned with respect to one another, e.g. for space correlations (event A taking place 50 meters from Event B ...
dblp:conf/refsq/GariglianoPM18
fatcat:bqpj4kcj6vd4xotyprhyskv72e
Temporal data representation, normalization, extraction, and reasoning: A review from clinical domain
2016
Computer Methods and Programs in Biomedicine
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However, temporal data representation, normalization, extraction and reasoning are very important in order to mine such massive data and therefore for constructing the clinical timeline. ...
The review emphasis on the current existing gap between present methods and the semantic web technologies and catch up with the possible combinations. ...
Many efforts have picked up from the latest works on reasoning about temporal relations. ...
doi:10.1016/j.cmpb.2016.02.007
pmid:27040831
pmcid:PMC4837648
fatcat:a75g25csqzdvlkfusbbgwmxigq
Literature survey of temporal data models
2017
International Journal of Latest Trends in Engineering and Technology
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going on from last two decades. ...
Attribute values are functions from temporal elements onto attribute value domain, but not on the same temporal
element. Hence, lack in temporal homogeneity. ...
doi:10.21172/1.841.47
fatcat:odbedlm2zrabrkqf3xnjroei5q
Recognizing Explicit and Implicit Hate Speech Using a Weakly Supervised Two-path Bootstrapping Approach
[article]
2018
arXiv
pre-print
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Applying this model on a large quantity of tweets collected before, after, and on election day reveals motivations and patterns of inflammatory language. ...
To address various limitations of supervised hate speech classification methods including corpus bias and huge cost of annotation, we propose a weakly supervised two-path bootstrapping approach for an ...
Tackling Semantic Drifts Semantic drift is the most challenging problem in distant supervision and bootstrapping. ...
arXiv:1710.07394v2
fatcat:te3sqzclpbbqpo67mmq4w247ni
Where Does It Exist: Spatio-Temporal Video Grounding for Multi-Form Sentences
2020
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Thus, we then propose a novel Spatio-Temporal Graph Reasoning Network (STGRN) for this task. ...
First, we build a spatiotemporal region graph to capture the region relationships with temporal object dynamics, which involves the implicit and explicit spatial subgraphs in each frame and the temporal ...
Different from them, our spatio-temporal region graph not only involves the implicit and explicit spatial subgraphs in each frame, but also includes a temporal dynamic subgraph across frames. ...
doi:10.1109/cvpr42600.2020.01068
dblp:conf/cvpr/ZhangZZWLG20
fatcat:umcnf6qsajcezfx6k2sa2a6t5e
RPI-BLENDER TAC-KBP2013 Knowledge Base Population System
2013
Text Analysis Conference
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This year the RPI-BLENDER team participated in the following four tasks: English Entity Linking, Regular Slot Filling, Temporal Slot Filling and Slot Filling Validation. ...
In addition, we submitted two additional runs using temporal reasoning with event ordering constraints, based on collaboration with UIUC (Do et al., 2012) . ...
the distant supervision assumption). ...
dblp:conf/tac/YuLCLHCJZR13
fatcat:prighf7bu5gd5gti5uz35hmh5m
Embedding Time Expressions for Deep Temporal Ordering Models
2019
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
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on an automatically collected dataset with more frequent event-timex interactions. 1 ...
We evaluate the utility of these embeddings in the context of a strong neural model for event temporal ordering, and show a small increase in performance on the MATRES dataset and more substantial gains ...
Additionally, to evaluate the full potential of the proposed approach, we construct another dataset with more frequent event-timex interactions using distant supervision. ...
doi:10.18653/v1/p19-1433
dblp:conf/acl/GoyalD19
fatcat:xlg4anjlsjboxiesyuitypw5ie
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