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the grammar is the general dart of the syntactic box , the part concerned with syntactic structures---this grammar consists of a lexicon which pairs words or phrases with regular expression functions | 1 |
to this end , we use conditional random fields---we trained linear-chain conditional random fields as the baseline | 1 |
berland and charniak used a similar method for extracting instances of meronymy relation---berland and charniak proposed a similar method for part-whole relations | 1 |
furthermore , the unsupervised version of our autoencoder show comparable performance with the supervised baseline models and in some cases outperforms them---similarity between their hidden representations shows comparable performance with the state-of-the-art supervised models and in some cases outperforms them | 1 |
we proposed a novel japanese pas analysis model that exploits a semi-supervised adversarial training---in this paper , we propose to use a hierarchical bidirectional long short-term memory ( bi-lstm ) network | 0 |
in addition , we build another word alignment model for l1 and l2 using the small l1-l2 bilingual corpus---then , with l3 as a pivot language , we can build a word alignment model for l1 and l2 | 1 |
we now review the path ranking algorithm introduced by lao and cohen---then we review the path ranking algorithm introduced by lao and cohen | 1 |
semantic parsing is the task of mapping natural language sentences to a formal representation of meaning---we have used rouge-1 , which gives good results with standard summaries | 0 |
wordnet is a key lexical resource for natural language applications---unfortunately , wordnet is a fine-grained resource , which encodes possibly subtle sense distictions | 1 |
to generate these trees , we employ the stanford pos tagger 8 and the stack version of the malt parser---for all three systems , we used the stanford corenlp package to perform lemmatization and pos tagging of the input sentences | 1 |
we used the google news pretrained word2vec word embeddings for our model---were confirmed experimentally , further discussions of four points , which we describe in the next section , are necessary for a more accurate summary evaluation | 0 |
snow et al were among the first to use mturk to obtain data for several nlp tasks , such as textual entailment and word sense disambiguation---we measure translation quality via the bleu score | 0 |
intuitively such inference rules should be effective for recognizing textual entailment---we have identified important issues encountered in using inference rules for textual entailment | 1 |
the rise of social media such as blogs and microblogs has fueled interest in sentiment analysis---with the rise of social media , more and more user generated sentiment data have been shared on the web | 1 |
erkan and radev and mihalcea introduced algorithms for unsupervised extractive summarization that rely on the application of iterative graph-based ranking algorithms , such as pagerank and hits---the trigram language model is implemented in the srilm toolkit | 0 |
the language model is a 5-gram with interpolation and kneser-ney smoothing---we have used the srilm with kneser-ney smoothing for training a language model for the first stage of decoding | 1 |
our framework is based on the observation that ‘ from ... to ’ -like patterns can encode connectedness in very precise manner---we start from a different pattern , ‘ from . . . to ’ , which helps in discovering transport or connectedness | 1 |
the toolkit enables the use of structural kernels in svm-light---we use svm-light-tk 5 , which enables the use of structural kernels | 1 |
then , in section 3 , we introduce our joint query annotation method---the process of identifying the correct meaning , or sense of a word in context , is known as word sense disambiguation ( wsd ) | 0 |
this representation can be obtained automatically using the stanford parser , which in addition provides a dependency identifying the root word in a sentence---these features consist of parser dependencies obtained from the stanford dependency parser for the context of the target word | 1 |
for each word , three vectors are obtained---for each word , we obtain three word embedding vectors | 1 |
the set of features defined by them form a feature space---the set of features is defined by a human | 1 |
this means in practice that the language model was trained using the srilm toolkit---a 4-gram language model was trained on the target side of the parallel data using the srilm toolkit from stolcke | 1 |
xiong et al integrated two discriminative feature-based models into a phrase-based smt system , which used the semantic predicateargument structure of the source language---xiong et al incorporated the semantic structures into phrasebased smt by adding syntactic and semantic features to their translation model | 1 |
to capture this similarity , we make use of a novel sentiment-augmented variant of word sequence kernels---we use a novel variant of word sequence kernels to measure sentence similarity | 1 |
the types of events to extract are known in advance---in this current work , the type of event to extract is known in advance | 1 |
the obtained scfs comprise the total 163 scf types which are originally based on the scfs in the anlt and comlex dictionaries---for both translation directions , we trained supervised neural mt and statistical mt systems , and combined them through n-best list reranking using different informative features as proposed by marie and fujita | 0 |
we use the logistic regression classifier in the skll package , which is based on scikit-learn , optimizing for f 1 score---we train and evaluate a l2-regularized logistic regression classifier with the liblin-ear solver as implemented in scikit-learn | 1 |
for example hirschberg and litman found that intonational phrasing and pitch accent play a role in disambiguating cue phrases , and hence in helping determine discourse structure---collobert and weston used convolutional neural networks in a multitask setting , where their model is trained jointly for multiple nlp tasks with shared weights | 0 |
we present new results from an evaluation with real users , for a reinforcement learning framework to learn user-adaptive referring expression generation policies from datadriven user simulations---we present a reinforcement learning framework to learn user-adaptive referring expression generation policies from datadriven user simulations | 1 |
we adopted the case-insensitive bleu-4 as evaluation metric and ran mert three times to alleviate the instability---we used the case-insensitive bleu-4 to evaluate translation quality and run mert three times | 1 |
in this paper , we treat a . ( sets of cognates ) as given , and focus on problems b. and c.---in this paper , we treat a . ( sets of cognates ) as given , and focus on problems | 1 |
dependency parsing is a fundamental task for language processing which has been investigated for decades---dependency parsing is a simpler task than constituent parsing , since dependency trees do not have extra non-terminal nodes and there is no need for a grammar to generate them | 1 |
lapata also addresses regular polysemy in the generative lexicon framework---lapata uses a large corpus to acquire the meanings of polysemous adjectives | 1 |
semantic role labeling ( srl ) has been defined as a sentence-level natural-language processing task in which semantic roles are assigned to the syntactic arguments of a predicate ( cite-p-14-1-7 )---we present a method to induce an embedded frame lexicon in an minimally supervised fashion | 0 |
furthermore , we train a 5-gram language model using the sri language toolkit---in this paper , we suggest a method that automatically constructs an ne tagged corpus from the web | 0 |
the proposed framework obtains comparable performance regarding standard discoursing parsing evaluations when compared against current state-of-art systems---distributed vectors for discourse analysis obtains comparable performance compared with current state-of-art discourse parsing system | 1 |
the selection approach has only been used in conversational systems that are not task-oriented such as negotiating agents , question answering characters , and virtual patients---the selection approach to generation has only been used in conversational systems that are not task-oriented such as negotiating agents , question answering characters , and virtual patients | 1 |
the data in all these languages is obtained from the conll 2006 shared task on multilingual dependency parsing---the data sets used are taken from the conll-x shared task on multilingual dependency parsing | 1 |
chinese is a language without natural word delimiters---this is because chinese is a pro-drop language ( cite-p-21-3-1 ) that allows the subject to be dropped in more contexts than english does | 1 |
distributional pattern or dependency with syntactic patterns is also a prominent source of data input---the distributional pattern or dependency with syntactic patterns is also a prominent source of data input | 1 |
the various models developed are evaluated using bleu and nist---we will briefly describe the system and then the additions we made to cope with the new task | 0 |
finally , the ape system was tuned on the development set , optimizing ter with minimum error rate training---for adjusting feature weights , the mert method was applied , optimizing the bleu-4 metric obtained on the development corpus | 1 |
titov and henderson extended the incremental sigmoid belief networks to a generative latent variable model for dependency parsing---similarly , titov and henderson added a word parameter to the shift transition to get a joint model of word strings and dependency trees | 1 |
we implemented this model using the srilm toolkit with the modified kneser-ney discounting and interpolation options---we use srilm to train a 5-gram language model on the target side of our training corpus with modified kneser-ney discounting | 0 |
we adapted the moses phrase-based decoder to translate word lattices---cite-p-18-1-3 later proposed a constituency parser to handle nested entities | 0 |
content plans are represented intuitively by a set of grammar rules that operate on the document level and are acquired automatically from training data---document plans are induced automatically from training data and are represented intuitively by pcfg rules | 1 |
for the semantic language model , we used the srilm package and trained a tri-gram language model with the default goodturing smoothing---a widely used topic modeling method is the latent dirichlet allocation model , which is proposed by blei | 0 |
similarly , turian et al collectively used brown clusters , cw and hlbl embeddings , to improve the performance of named entity recognition and chucking tasks---we apply the moses tok- enizer and byte-pair encoding | 0 |
luong et al , 2013 ) utilized recursive neural networks in which inputs are morphemes of words---luong et al , 2013 ) generates better word representation with recursive neural network | 1 |
we tune model weights using minimum error rate training on the wmt 2008 test data---we adapt the minimum error rate training algorithm to estimate parameters for each member model in co-decoding | 1 |
reasoning is a crucial part of natural language argumentation---reasoning is the process of thinking in a logical way to form a conclusion | 1 |
for the the pair in ( 1 ) , the two instances of the variation nucleus satisfy the non-fringe heuristic because they are properly contained within the identical variation n-gram ( with the and points on either side )---in ( 1 ) , the two instances of the variation nucleus satisfy the non-fringe heuristic because they are properly contained within the identical variation | 1 |
they have also demonstrated that a similar approach can be utilized to estimate user expertise levels---liu et al present a pairwise competition based method for estimating user expertise scores | 1 |
our final event-driven model obtains the best result on this dataset---evaluation shows that our model achieves the best performance | 1 |
our model learns the policy on selecting antecedents in a sequential manner , leveraging effective information provided by the earlier predicted antecedents---our model learns the policy of selecting antecedents in a sequential manner , where useful information provided by earlier predicted antecedents could be utilized for making later coreference decisions | 1 |
it is reported in , that more than 4 million distinct out-of-vocabulary tokens are found in the edinburgh twitter corpus---it is reported in that more than four million distinct out-of-vocabulary tokens occur in the edinburgh twitter corpus | 1 |
the increasing number of documents and categories , however , often hampers the development of practical classification systems , mainly due to statistical , computational , and representational problems---however , the increasing number of documents and categories often hamper the development of practical classification systems , mainly by statistical , computational , and representational problems | 1 |
when used as the underlying input representation , word vectors have been shown to boost the performance in nlp tasks---in particular , the vector-space word representations learned by a neural network have been shown to successfully improve various nlp tasks | 1 |
a 5-gram language model with kneser-ney smoothing was trained with srilm on monolingual english data---we use sri language model toolkit to train a 5-gram model with modified kneser-ney smoothing on the target-side training corpus | 0 |
coreference resolution is the task of partitioning a set of mentions ( i.e . person , organization and location ) into entities---in this work , we use the expectation-maximization algorithm | 0 |
for this labeling , we estimate translation quality by the translation edit rate ter metric---in order to measure translation quality , we use bleu 7 and ter scores | 1 |
for language model , we used sri language modeling toolkit to train a 4-gram model with modified kneser-ney smoothing---we trained a 4-gram language model with kneser-ney smoothing and unigram caching using the sri-lm toolkit | 1 |
morante et al and daelemans pioneered the research on scope learning by formulating it as a chunking problem , which classifies the words of a sentence as being inside or outside the scope of a cue---morante et al and morante and daelemans pioneered the research on negation scope finding by formulating it as a chunking problem , which classifies the words of a sentence as being inside or outside the scope of a negation signal | 1 |
in , the authors try to automatically classify speeches , from the us congress debates , as supporting or opposing a given topic by taking advantage of the voting records of the speakers---in , the authors use the transcripts of debates from the us congress to automatically classify speeches as supporting or opposing a given topic by taking advantage of the voting records of the speakers | 1 |
experimental results over evaluation sets of noun phrases from multiple sources demonstrate that interpretations extracted from queries have encouraging coverage and precision---experimental results over evaluation sets of noun phrases from multiple sources demonstrate that interpretations can be extracted from queries | 1 |
we used the dependency parser from the stanford corenlp---we use stanford corenlp for feature generation | 1 |
for pos-tagging , we used the stanford pos-tagger---for pos-tagging , we used the stanford pos tagger | 1 |
we compare the final system to moses 3 , an open-source translation toolkit---we use the popular moses toolkit to build the smt system | 1 |
in order to train the argument identification and role label disambiguation classifiers , we used the english portion of the conll 2009 shared task---for the evaluation , we use the dependency treebanks for multiple languages from the conll-shared task 2009 2 3 are used for training the english models | 1 |
the research area that deals with the computational treatment of opinion , sentiment and subjectivity in texts is called sentiment analysis ( cite-p-12-1-7 )---sentiment analysis ( cite-p-12-3-17 ) is a popular research topic which has a wide range of applications , such as summarizing customer reviews , monitoring social media , and predicting stock market trends ( cite-p-12-1-4 ) | 1 |
all experiments are implemented using the weka software package---the experiment was conducted using the weka toolkit | 1 |
we specifically examine two levels of representation of conversation segments and two different ways of modeling long distance relations between language constituents---in this paper , we systematically examine different representations of the conversation segment and different modeling of long distance relations between language constituents | 1 |
we use the opennlp pos tagger 4 to obtain pos tags and employ the maltparser for dependency parsing---coreference resolution is the task of partitioning a set of entity mentions in a text , where each partition corresponds to some entity in an underlying discourse model | 0 |
andrzejewski et al proposed a method for generating coherent topics which used a mixture of dirichlet distributions to incorporate domain knowledge---andrzejewski et al and mimno and mccallum both attempt to incorporate generalized domain knowledge into generative topic models using priors | 1 |
evaluation results for both models are presented , through which we demonstrate that the tree crf -based model performs better than the direct inversion model---we use srilm toolkit to build a 5-gram language model with modified kneser-ney smoothing | 0 |
we have provided just such a framework for improving parsing performance---the targetside 4-gram language model was estimated using the srilm toolkit and modified kneser-ney discounting with interpolation | 0 |
relation extraction is the task of finding semantic relations between two entities from text---relation extraction ( re ) is the task of determining semantic relations between entities mentioned in text | 1 |
we used the phrase-based smt model , as implemented in the moses toolkit , to train an smt system translating from english to arabic---we use the open source moses phrase-based mt system to test the impact of the preprocessing technique on translation quality | 1 |
coreference resolution is the problem of partitioning a sequence of noun phrases ( or mentions ) , as they occur in a natural language text , into a set of referential entities---coreference resolution is the process of determining whether two expressions in natural language refer to the same entity in the world | 1 |
relation extraction is the task of finding relationships between two entities from text---relation extraction is a subtask of information extraction that finds various predefined semantic relations , such as location , affiliation , rival , etc. , between pairs of entities in text | 1 |
sentiment analysis is a natural language processing task whose aim is to classify documents according to the opinion ( polarity ) they express on a given subject ( cite-p-13-8-14 )---in this paper , we study a novel approach for named entity recognition ( ner ) and mention detection ( md ) | 0 |
sasano et al proposed a lexicalized probabilistic model for zero anaphora resolution , which adopted an entity-mention model and simultaneously resolved predicateargument structures and zero anaphora---sasano et al proposed a probabilistic predicate-argument structure analysis model including zero endophora resolution by using widecoverage case frames constructed from a web corpus | 1 |
in order to better handle rare words , we initialized our word embeddings using 200 dimensional vectors trained with glove on data from wikipedia---since the similarity calculations in our framework involves vectorial representations for each word , we trained 300 dimensional glove vectors on the chinese gigaword corpus | 1 |
morante et al also discuss the need for corpora which cover other domains---our models measure cross-lingual similarity of the coreference chains to make clustering decisions | 0 |
we use lists of discourse markers compiled from the penn discourse treebank and from to identify such markers in the text---we use a list of such connectives compiled by and study the statistics of our corpus to discover the discourse relations | 1 |
this paper proposes a method for dependency parsing of monologue sentences based on sentence segmentation---we obtained both phrase structures and dependency relations for every sentence using the stanford parser | 0 |
in this model , the question subject is the primary part of the question representation , and the question body information is aggregated based on similarity and disparity with the question subject---in community questions , we propose to treat the question subject as the primary part of the question , and aggregate the question body information based on similarity and disparity with the question subject | 1 |
in this work , we show that such promise exists for coreference also---sentiment analysis is a natural language processing task whose aim is to classify documents according to the opinion ( polarity ) they express on a given subject ( cite-p-13-8-14 ) | 0 |
word sense disambiguation ( wsd ) is the task of identifying the correct sense of an ambiguous word in a given context---word sense disambiguation ( wsd ) is the task of automatically determining the correct sense for a target word given the context in which it occurs | 1 |
the disadvantage of word-to-word translation is overcome by phrase-based translation and log-linear model combination---the phrase-based approach developed for statistical machine translation is designed to overcome the restrictions of many-to-many mappings in word-based translation models | 1 |
lagrangian relaxation is a classical technique in combinatorial optimization ( cite-p-15-1-10 )---rosengrant proposed an analysis method named gaze scribing where eye-tracking data is combined with subjects thought process derived by the think-aloud protocol | 0 |
we use the opennlp pos tagger 4 to obtain pos tags and employ the maltparser for dependency parsing---for this type of syntactic representation , we exploit the maltparser platform , via which we have trained a memory-based dependency parser for greek | 1 |
for nominal predicates , the system makes use of a common sense reasoning module that builds on conceptnet---socher et al , 2012 ) presented a recursive neural network for relation classification to learn vectors in the syntactic tree path connecting two nominals to determine their semantic relationship | 0 |
goldwater et al used hierarchical dirichlet processes to induce contextual word models---we trained a 3-gram language model on all the correct-side sentences using kenlm | 0 |
our first layer was a 200-dimensional embedding layer , using the glove twitter embeddings---we used the 300-dimensional glove word embeddings learned from 840 billion tokens in the web crawl data , as general word embeddings | 1 |
in the joint modelling approaches , a sentiment topic is usually modelled as a sentiment label-word distribution , analogous to the topic-word distribution in standard topic models---after imitation learning with user teaching improves the model performance further , not only on the dialogue policy | 0 |
in recent years there has been a growing interest in crowdsourcing methodologies to be used in experimental research for nlp tasks---in this paper , we re-embed pre-trained word embeddings with a stage of manifold learning | 0 |
xia et al automatically extracted conversion rules from a target treebank and proposed strategies to handle the case when more than one conversion rule are applicable---in this paper , we propose a novel framework , companion teaching , to include a human teacher in the dialogue policy training loop | 0 |
our model combines the textual entailment paradigm within the exploration process , with application to the healthcare domain---we follow berant et al . ’ s proposal , and present a novel entailment-based text exploration system , which we applied to the healthcare domain | 1 |
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