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in contrast , the ordering decisions are only influenced by languages with similar properties---and therefore should only be influenced by languages with similar properties | 1 |
the second order algorithm of carreras uses in addition to mcdonald and pereira the child of the dependent occurring in the sentence between the head and the dependent , and the an edge to a grandchild---the second order algorithm of carreras uses in addition to mcdonald and pereira the child of the dependent occurring in the sentence between the head and the dependent as well as the edge from the dependents to a grandchild | 1 |
we compared sn models with two different pre-trained word embeddings , using either word2vec or fasttext---we then used word2vec to train word embeddings with 512 dimensions on each of the prepared corpora | 1 |
the results indicate that a combination of the well-nestedness constraint and a parametric constraint on discontinuity gives a very good fit with the linguistic data---shows , that a combination of the well-nestedness constraint and parametric constraints on discontinuity ( formalized either as gap degree or edge degree ) gives a very good fit with the empirical linguistic data | 1 |
in this paper , we proposed a much more efficient and accurate model for fully unsupervised word segmentation---in order to deal with this problem , we perform word alignment in two directions as described in | 0 |
ongoing work aim to improve the rule-based method and combine it with a supervised machine learning algorithm---supervised machine learning was applied to monitor the performance of the rule-based method | 1 |
we used the srilm toolkit to train a 4-gram language model on the english side of the training corpus---erk and pad贸 incorporate inverse selectional preferences into their contextualization function | 0 |
we report the findings of the complex word identification task of semeval 2016---we have described the findings of the complex word identification task of semeval 2016 | 1 |
the spanish experiments transfer from english to spanish using the spanish portion of the europarl corpus---for the english-german experiments , the translation system was trained and tested using a part of the europarl corpus | 1 |
1 eojeol is a korean spacing unit which consists of one or more eumjeols ( morphemes )---2 an eojeol is a korean spacing unit ( similar to an english word ) , which usually consists of one or more stem morphemes and a series of functional morphemes | 1 |
neural networks have recently gained much attention as a way of inducing word vectors---and while discourse parsing is a document level task , discourse segmentation is done at the sentence level , assuming that sentence boundaries are known | 0 |
m 2 was the metric used for the 2013 and 2014 conll gec shared tasks , ng et al , 2014---m 2 was the metric used for the 2013 and 2014 conll gec shared tasks ng et al , 2014 ) | 1 |
in this work , we propose an automatic domain partitioning approach that aims at providing better domain identities for mdl---in this paper , we propose an automatic domain partition ( adp ) method that provides better domain identities for multi-domain learning | 1 |
this syntactic information is obtained from the stanford parser---blitzer et al proposed structural correspondence learning to identify the correspondences among features between different domains via the concept of pivot features | 0 |
intuitively , hand-crafted thesaurus could provide reliable related terms , which would help improve the performance---thesauri , hand-crafted thesauri , such as wordnet , could provide more reliable terms for query expansion | 1 |
a novel aspect of our work is also the use of web context features for medication detection---part of our research addresses the problem of medication detection from informal text | 1 |
the original pmg implementation has utilised conditional random fields , due to the considerable representation capabilities of this model---the tagger is based on the implementation of conditional random fields in the mallet toolkit | 1 |
vijay-shanker and weir introduce a compilation of tag to linear indexed grammars that makes the derivation process explicit---the tag-to-lig compilation proposed by vijay-shanker and weir produces lig rules that simulate a traversal of the derived tree produced by the original tag grammar | 1 |
we used the brat annotation tool for annotating the corpus---we performed the annotation on the brat annotation tool | 1 |
similarly , hua wu applied synonyms relationship between two different languages to automatically acquire english synonymous collocation---parameters are initialized using the method described by glorot and bengio | 0 |
we have introduced pre-post-editing , a minimalist interactive machine translation paradigm where a user is only asked to spot text fragments that may be used in the final translation---we introduce pre-post-editing , possibly the most basic form of interactive translation , as a touch-based interaction with iteratively improved translation | 1 |
we use the term-sentence matrix to train a simple generative topic model based on lda---scorer can be used as a rich feature function for story generation or a reward function for systems that use reinforcement learning to learn to generate stories | 0 |
we used the sri language modeling toolkit to calculate the log probability and two measures of perplexity---we used the srilm software 4 to build langauge models as well as to calculate cross-entropy based features | 1 |
in this paper we explore the utility of the navigation map , a graphical representation of the discourse structure---here we investigate the benefits of displaying the discourse structure information | 1 |
for the svm classifier we use the python scikitlearn library---we use the svm implementation from scikit-learn , which in turn is based on libsvm | 1 |
we implemented our method in a phrase-based smt system---we use the moses toolkit to train our phrase-based smt models | 1 |
our system is notable in that for tasks c – f , they operated on raw text while all other systems used tagged events and temporal expressions in the corpus as input---for task c-f we operated on features automatically computed from raw text rather than using the tagged events and temporal expressions in the corpus | 1 |
in this paper , we exploit structured neural models for open targeted sentiment---under the neural setting , we find that it is preferable to solve open targeted sentiment | 1 |
we use bleu to evaluate translation quality---we use case-sensitive bleu to assess translation quality | 1 |
we use word embedding pre-trained on newswire with 300 dimensions from word2vec---we use the word2vec tool with the skip-gram learning scheme | 1 |
mihalcea et al use both corpusbased and knowledge-based measures of the semantic similarity between words---the 5-gram kneser-ney smoothed language models were trained by srilm , with kenlm used at runtime | 0 |
in this paper , we attack a deceptively simple form of the problem : understanding what a customer wants when ordering at a restaurant---in this paper we tackle a unique and important problem of extracting a structured order from the conversation a customer has with an order | 1 |
to avoid this problem , we adopt the approach proposed in , the error inflation method , and add artificial article errors in the training data based on the error distribution on the training set---to avoid this problem , we adopt the approach proposed in rozovskaya et al , the error inflation method , and add artificial article errors to the training data based on the error distribution on the training set | 1 |
we evaluated using the two widely used performance measures for coreference resolution -muc score and b 3---jiang et al put forward a ptc framework based on support vector machine | 0 |
the parameters of the log-linear model are tuned by optimizing bleu on the development data using mert---word alignment is the problem of annotating parallel text with translational correspondence | 0 |
the work described in this paper is based on the smt framework of hierarchical phrase-based translation---the hierarchical phrase-based model is capable of capturing rich translation knowledge with the synchronous context-free grammar | 1 |
hatzivassiloglou and mckeown proposed a method for identifying the word polarity of adjectives---hatzivassiloglou and mckeown used a log-linear regression model to predict the similarity of conjoined adjectives | 1 |
yao et al and riedel et al present a similar task of predicting novel relations between freebase entities by appealing to a large collection of open ie extractions---in this paper , we present an algorithm that detects and corrects modification and abridged speech repairs | 0 |
the toolkit provides implementations of existing graph-based wsi algorithms , but can also be extended with new algorithms---the toolkit enables the objective comparison of wsi algorithms within an end-user application | 1 |
moreover , our approach gives some intuitions on how target-specific sentence representations can be achieved from its word constituents---in this paper , we propose a framework that automatically induces target-specific sentence representations over tree structures | 1 |
latent dirichlet allocation is one of the widely adopted generative models for topic modeling---the parameters of the log-linear model were tuned by optimizing bleu on the development set using the batch variant of margin infused relaxed algorithm by cherry and foster | 0 |
we use the popular moses toolkit to build the smt system---the smt systems were built using the moses toolkit | 1 |
dependency parsing is the task of predicting the most probable dependency structure for a given sentence---this paper presented a negative result about importance weighting for unsupervised domain adaptation of pos taggers | 0 |
we used trigram language models with interpolated kneser-kney discounting trained using the sri language modeling toolkit---for all models , we use the 300-dimensional glove word embeddings | 0 |
in section 4 , we develop a correct , complete and terminating extension of earley 's algorithm for the patr-ii formalism using the restriction notion---we presented a complete , correct , terminating extension of earley ' s algorithm that uses restriction | 1 |
coreference resolution is a key task in natural language processing ( cite-p-13-1-8 ) aiming to detect the referential expressions ( mentions ) in a text that point to the same entity---coreference resolution is the task of grouping all the mentions of entities 1 in a document into equivalence classes so that all the mentions in a given class refer to the same discourse entity | 1 |
semantic parsing is the task of translating natural language utterances into a machine-interpretable meaning representation---named entity recognition ( ner ) is a fundamental information extraction task that automatically detects named entities in text and classifies them into predefined entity types such as person , organization , gpe ( geopolitical entities ) , event , location , time , date , etc | 0 |
we trained an english 5-gram language model using kenlm---choudhury et al proposed a hidden markov model based text normalization approach for sms texts and texting language | 0 |
we use liblinear 9 to solve the lr and svm classification problems---we use liblinear with l2 regularization and default parameters to learn a model | 1 |
sentiment classification is a task of predicting sentiment polarity of text , which has attracted considerable interest in the nlp field---sentiment classification is the task of classifying an opinion document as expressing a positive or negative sentiment | 1 |
we have presented a framework for abstractive summarization of product reviews based on discourse structure---we propose a novel abstractive summarization framework that generates an aspect-based abstract from multiple reviews of a product | 1 |
we use the stanford parser to generate the grammar structure of review sentences for extracting syntactic d-features---we use the berkeley probabilistic parser to obtain syntactic trees for english and its adapted version for french | 1 |
we propose a multipass , coarse-to-fine approach in which the language model complexity is incrementally introduced---in this paper , we propose a new , coarse-to-fine , multipass approach which allows much greater speedups | 1 |
in this study , we focus on improving the corpus-based method for cross-lingual sentiment classification of chinese product reviews by developing novel approaches---in this study , we focus on the problem of cross-lingual sentiment classification , which leverages only english training data for supervised sentiment classification of chinese product reviews | 1 |
we used the srilm toolkit to train a 4-gram language model on the english side of the training corpus---further , we apply a 4-gram language model trained with the srilm toolkit on the target side of the training corpus | 1 |
in a different work , banerjee and lavie argued that the measured reliability of metrics can be due to averaging effects but might not be robust across translations---banerjee and lavie argued that the reliability of metrics at the document level can be due to averaging effects but might not be robust across sentence translations | 1 |
ultimately , the purpose of this work is to improve the quality of machine translation systems---purpose of our work is to improve the performance of statistical machine translation systems | 1 |
the meta-net project aims to ensure equal access to information by all european citizens---in our experiment , using glpk ’ s branch-and-cut solver took 0 . 2 seconds to produce optimal ilp solutions for 1000 sentences | 0 |
semantic role labeling ( srl ) is defined as the task to recognize arguments for a given predicate and assign semantic role labels to them---semantic role labeling ( srl ) is the task of identifying semantic arguments of predicates in text | 1 |
magatti et al introduced an approach for labelling topics that relied on two hierarchical knowledge resources labelled by humans , the google directory and the openoffice english thesaurus---magatti et al proposed a method for labelling topics induced by hierarchical topic modelling , based on ontological alignment with the google directory hierarchy , and optionally expanding topics based on a thesaurus or wordnet | 1 |
for the tree-based system , we applied a 4-gram language model with kneserney smoothing using srilm toolkit trained on the whole monolingual corpus---we use srilm toolkit to train a trigram language model with modified kneser-ney smoothing on the target side of training corpus | 1 |
grefenstette and sadrzadeh learn matrices for verbs in a categorical model---grefenstette and sadrzadeh use a similar approach with matrices for relational words and vectors for arguments | 1 |
we proposed an svm-based approach for soundbite speaker name recognition and examined various linguistic features---we evaluated our mt output using the surface based evaluation metrics bleu , meteor , cder , wer , and ter | 0 |
the target language model was a standard ngram language model trained by the sri language modeling toolkit---the sri language modeling toolkit was used to build 4-gram word-and character-based language models | 1 |
finally , based on recent results in text classification , we also experiment with a neural network approach which uses a long-short term memory network---like recent work , we use the lstm variant of recurrent neural networks as language modeling architecture | 1 |
however , if we only use local features , then we can not model long-distance dependencies---if the anaphor is a pronoun , the cache is searched for a plausible referent | 0 |
we also investigated ways of effectively applying these rules---in this paper , we explore ways of improving an inference rule | 1 |
coreference resolution is a challenging task , that involves identification and clustering of noun phrases mentions that refer to the same real-world entity---coreference resolution is a key task in natural language processing ( cite-p-13-1-8 ) aiming to detect the referential expressions ( mentions ) in a text that point to the same entity | 1 |
in this work , we propose a multi-sentence qa challenge in which questions can be answered only using information from multiple sentences---we have presented multirc , a reading comprehension dataset in which questions require reasoning over multiple sentences to be answered | 1 |
several researchers ( cite-p-20-1-4 , cite-p-20-3-1 , van der cite-p-20-3-9 ) have used large monolingual corpora to extract distributionally similar words---the graph-based reg algorithm , for example , models preferences in terms of costs , where cheaper is more preferred | 0 |
solorio and liu pioneered the work on cs and developed an ml classifier to predict code-switching points in spanishenglish---semantic role labeling ( srl ) is the process of producing such a markup | 0 |
noun phrase coreference resolution is the task of determining which noun phrases in a text or dialogue refer to the same discourse entities---noun phrase coreference resolution is the task of determining which noun phrases in a text or dialogue refer to the same real-world entities | 1 |
word sense disambiguation ( wsd ) is a problem of finding the relevant clues in a surrounding context---pp yields a significant improvement over a state-of-the-art system on bridging anaphora resolution in isnotes ( cite-p-12-3-7 ) | 0 |
in addition , we compare against the morfessor categories-map system---as a baseline for this comparison , we use morfessor categories-map | 1 |
the results are reported in bleu and ter scores---results were evaluated with both bleu and nist metrics | 1 |
human evaluation is a key aspect of many nlp technologies---while human evaluation is the most accurate way to compare systems , approximate automatic evaluation becomes critical during system development | 1 |
relation extraction is the task of finding relations between entities in text , which is useful for several tasks such as information extraction , summarization , and question answering ( cite-p-14-3-7 )---relation extraction is a challenging task in natural language processing | 1 |
classes can be induced directly from the corpus or taken from a manually crafted taxonomy---another stream of work tries to identify domain-specific words to improve crossdomain classification | 0 |
several measures to identify word pairs that stand in an instance-class relationship by comparing their vectors have been proposed in the recent distributional semantics literature---more recently , a number of techniques for detecting lexical entailment have been developed using distributional semantics | 1 |
the decoding weights were optimized with minimum error rate training---the feature weights are tuned to optimize bleu using the minimum error rate training algorithm | 1 |
we use glove 300-dimension embedding vectors pre-trained on 840 billion tokens of web data---we use glove vectors with 100 dimensions trained on wikipedia and gigaword as word embeddings | 1 |
we used the cdec decoder to extract word alignments and the baseline hierarchical grammars , mert tuning , and decoding---we used cdec as our hierarchical phrase-based decoder , and tuned the parameters of the system to optimize bleu on the nist mt06 corpus | 1 |
we use sri language model toolkit to train a 5-gram model with modified kneser-ney smoothing on the target-side training corpus---we train a kn-smoothed 5-gram language model on the target side of the parallel training data with srilm | 1 |
specifically , we used wordsim353 , a benchmark dataset , consisting of relatedness judgments for 353 word pairs---we used the wordsim353 test collection which consists of similarity judgments for word pairs | 1 |
experimental analyses show that the mappings learned cover most of the domain ontology , and provide good linguistic variation---the learned mappings provide good coverage of the domain ontology and exhibit good linguistic variation | 1 |
in section 3 we then describe the probabilistic taxonomy learning model introduced by---thus , event extraction is a difficult task and requires substantial training data | 0 |
distributional semantic models are employed to produce semantic representations of words from co-occurrence patterns in texts or documents---to address this shortcoming , developed the relaxed distant supervision assumption for multi-instance learning | 0 |
our main aim was not to build a complete model to handle all possible lm scenarios , but to present a “ proofof-concept ” study to test the potentialities of this approach---and our main aim is to show the potentialities of such approach rather than building a complete application for solving this problem | 1 |
for the second noise type , we propose ways to improve the integration of noisy entity type predictions into relation extraction---we show that a novel way of integrating noisy entity type predictions into a relation extraction model | 1 |
the berkeley parser was used to obtain syntactic annotations---the berkeley parser was employed for parsing the chinese sentences | 1 |
we use the logistic regression implementation of liblinear wrapped by the scikit-learn library---we used the implementation of random forest in scikitlearn as the classifier | 1 |
in the remainder of this paper , we describe a new architecture for interactive q/a---in this paper , we have presented f erret , an interactive q / a system which makes use of a novel q / a architecture | 1 |
subsequently we compare the model to previously proposed architectures and finally describe the experimental results on the performance of our model---we compare the model to previously proposed architectures and finally describe the experimental results on the performance of our model | 1 |
long short-term memory was introduced by hochreiter and schmidhuber to overcome the issue of vanishing gradients in the vanilla recurrent neural networks---the long short-term memory was first proposed by hochreiter and schmidhuber that can learn long-term dependencies | 1 |
recently , automatically solving math word problems has attracted several researchers---the two baseline methods were implemented using scikit-learn in python | 0 |
a pun is the exploitation of the various meanings of a word or words with phonetic similarity but different meanings---a pun is a form of wordplay in which a word suggests two or more meanings by exploiting polysemy , homonymy , or phonological similarity to another word , for an intended humorous or rhetorical effect | 1 |
for training the translation model and for decoding we used the moses toolkit---we used a phrase-based smt model as implemented in the moses toolkit | 1 |
an approximation proposed in is to extend the search node with the rnn hidden state , but to ignore the hidden state when deciding which nodes to recombine---we compare between caching the rnn hidden state and the approach proposed in , which stores the rnn hidden state in the search node | 1 |
seo et al focuses on sat geometry questions with text and diagram provided---seo et al solves a set of sat geometry questions with text and diagram provided | 1 |
an intuitive paradigm is to compute similarities between all the words or phrases of the two sentences---these models directly build an interaction space between two sentences | 1 |
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