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Found 22 papers, 0 papers with code
Linguist vs. Machine: Rapid Development of Finite-State Morphological Grammars
Sequence-to-sequence models have proven to be highly successful in learning morphological inflection from examples as the series of SIGMORPHON/CoNLL shared tasks have shown.
Identifying Predictive Causal Factors from News Streams
We propose a new framework to uncover the relationship between news events and real world phenomena.
Arabic Dialect Identification for Travel and Twitter Text
This paper presents the results of the experiments done as a part of MADAR Shared Task in WANLP 2019 on Arabic Fine-Grained Dialect Identification.
Unsupervised Word Influencer Networks from News Streams
We present Word Influencer Networks (WIN), a graph framework to extract longitudinal temporal relationships between any pair of informative words from news streams.
Relationship Extraction (Distant Supervised)
Stock Price Prediction
TeamDL at SemEval-2018 Task 8: Cybersecurity Text Analysis using Convolutional Neural Network and Conditional Random Fields
For subtask 1 We experimented with two category of word embeddings namely native embeddings and task specific embedding using Word2vec and Glove algorithms.
Hitachi at SemEval-2017 Task 12: System for temporal information extraction from clinical notes
This paper describes the system developed for the task of temporal information extraction from clinical narratives in the context of the 2017 Clinical TempEval challenge.
Can Syntax Help? Improving an LSTM-based Sentence Compression Model for New Domains
In this paper, we study how to improve the domain adaptability of a deletion-based Long Short-Term Memory (LSTM) neural network model for sentence compression.
Ranked #6 on
Sentence Compression
on Google Dataset
Coreference Annotation Scheme and Relation Types for Hindi
This paper describes a coreference annotation scheme, coreference annotation specific issues and their solutions through our proposed annotation scheme for Hindi.
