[PDF] Top 20 Introducing the SPMRL 2014 Shared Task on Parsing Morphologically rich Languages
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Introducing the SPMRL 2014 Shared Task on Parsing Morphologically rich Languages
... The shared task focused on parsing nine morphologically rich languages, from different typological language families, in both a constituent-based and a dependency-based ... See full document
7
Introducing the IMS Wrocław Szeged CIS entry at the SPMRL 2014 Shared Task: Reranking and Morpho syntax meet Unlabeled Data
... Constant, Rich´ard Farkas, Iakes Goenaga, Koldo Gojenola, Yoav Goldberg, Spence Green, Nizar Habash, Marco Kuhlmann, Wolfgang Maier, Joakim Nivre, Adam Przepiorkowski, Ryan Roth, Wolfgang Seeker, Yannick Versley, ... See full document
6
Proceedings of the First Joint Workshop on Statistical Parsing of Morphologically Rich Languages and Syntactic Analysis of Non Canonical Languages
... in parsing morphologically-rich languages and non-canonical language, with the goal of identifying cross- cutting issues in the annotation and parsing methodology, in the face of more ... See full document
10
Hindi Dependency Parsing using a combined model of Malt and MST
... etc.) languages are free-word-order and are also morphologically ...free-word-order languages can be handled better using the dependency based framework than the constituency based one (Bharati et ... See full document
8
The AI KU System at the SPMRL 2013 Shared Task : Unsupervised Features for Dependency Parsing
... We propose the use of the word categories and embeddings induced from raw text as auxil- iary features in dependency parsing. To in- duce word features, we make use of contex- tual, morphologic and orthographic ... See full document
8
Deep Neural Networks for Syntactic Parsing of Morphologically Rich Languages
... the SPMRL Shared Task 2014. (Hall et al., 2014) introduced an approach where, instead of propa- gating contextual information from the leaves of the tree to internal nodes in order to ... See full document
6
Proceedings of the Fourth Workshop on Statistical Parsing of Morphologically Rich Languages
... first shared task for parsing morphologically-rich languages, co-located with SPMRL ...the shared task for their contributions and of course our invited ... See full document
12
Exploring Confidence based Self training for Multilingual Dependency Parsing in an Under Resourced Language Scenario
... Choi, Rich´ard Farkas, Jen- nifer Foster, Iakes Goenaga, Koldo Gojenola Gal- letebeitia, Yoav Goldberg, Spence Green, Nizar Habash, Marco Kuhlmann, Wolfgang Maier, Joakim Nivre, Adam Przepi´orkowski, Ryan Roth, ... See full document
9
Character Composition Model with Convolutional Neural Networks for Dependency Parsing on Morphologically Rich Languages
... Pre-trained word embeddings can alleviate the OOV problem by expanding the vocabulary, but it does not model the morphological information. Instead of looking up word embeddings, many researchers propose to compose the ... See full document
7
Proceedings of the Second Workshop on Statistical Parsing of Morphologically Rich Languages
... the SPMRL tradition of ending the workshop with a panel ...a shared task on parsing MRLs, in the face of various challenges that emerge when going beyond English and the WSJ Penn ...from ... See full document
10
Exploring beam based shift reduce dependency parsing with DyALog: Results from the SPMRL 2013 shared task
... the SPMRL 2013 shared task: A cross-framework evalu- ation of parsing morphologically rich ...of Morphologically Rich Languages: Shared Task, ... See full document
10
Overview of the SPMRL 2013 Shared Task: A Cross Framework Evaluation of Parsing Morphologically Rich Languages
... encoded morphologically in ...the shared task is based on the Szeged Treebank, the largest morpho-syntactic and syntactic corpus manually annotated for ... See full document
37
Statistical Parsing of Morphologically Rich Languages (SPMRL) What, How and Whither
... into parsing mod- els, three types of challenges present themselves: Architecture and Setup: When attempting to parse complex word-forms that encapsulate both lexical and functional information, important archi- ... See full document
12
Proceedings of the ACL 2012 Joint Workshop on Statistical Parsing and Semantic Processing of Morphologically Rich Languages
... for SPMRL), and encompass several different parsing approaches and combinations thereof, including dependency parsing, PCFG-LA parsing, rule-based parsing and precision-grammar-based ... See full document
12
Translating into Morphologically Rich Languages with Synthetic Phrases
... The paper is structured as follows. We first present our “translate-and-inflect” model for pre- dicting lexical translations into morphologically rich languages given a source word and its context ... See full document
11
LAMB: A Good Shepherd of Morphologically Rich Languages
... There have been a large number of studies on En- glish, a morphologically simple language, that show that the effect of normalization, in particular stem- ming, is different for different applications. For in- ... See full document
11
Word Semantic Similarity for Morphologically Rich Languages
... 5.2. Stemming Rules Ranking Experiments In order to acquire a better picture of the effects of stem- ming and the resulting semantic distortion, we attempted to cover the largest possible set of words in our vocabu- lary ... See full document
7
Clinical Data Classification using Conditional Random Fields and Neural Parsing for Morphologically Rich Languages
... In this paper, we used CRFs to model conditional probability between tokens in prescriptions and output labels, dosage, dosage unit, frequency, and comments. This model is for Finnish prescrip- tions. Since Finnish is an ... See full document
7
Character Aware Decoder for Translation into Morphologically Rich Languages
... There is additionally a line of work on purely character-level NMT, which generates words one character at a time (Ling et al., 2015; Chung et al., 2016; Passban et al., 2018). While initial re- sults here were not ... See full document
12
Using POS Information for SMT into Morphologically Rich Languages
... Using POS tags as additional knowledge source, we enrich the English verbs such that they contain more information relevant for selecting the correct inflected form in the target languag[r] ... See full document
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