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"for all methods , the tweets were tokenized with the cmu twitter nlp tool ."
"the tweets were tokenized and part-ofspeech tagged with the cmu ark twitter nlp tool and stanford corenlp ."
"it was shown by nederhof et al that prefix probabilities can also be effectively computed for probabilistic tree adjoining grammars ."
"nederhof et al , for instance , show that prefix probabilities , and therefore surprisal , can be estimated from tree adjoining grammars ."
"first , kikuchi et al proposed a new long short-term memory network to control the length of the sentence generated by an encoder-decoder model in a text summarization task ."
"first , kikuchi et al tried to control the length of the sentence generated by an encoder-decoder model in a text summarization task ."
"with word confusion networks further improves performance ."
"the complexity is dominated by the word confusion network construction and parsing ."
"fofe can model the word order in a sequence based on a simple ordinally-forgetting mechanism , which uses the position of each word in the sequence ."
"fofe can model the word order in a sequence using a simple ordinally-forgetting mechanism according to the positions of words ."
"we ’ ve demonstrated that the benefits of unsupervised multilingual learning increase steadily with the number of available languages ."
"we found that performance improves steadily as the number of available languages increases ."
"dependency parsing consists of finding the structure of a sentence as expressed by a set of directed links ( dependencies ) between words ."
"dependency parsing is a way of structurally analyzing a sentence from the viewpoint of modification ."
"for each task , we provide separate training , development , and test datasets for english , arabic , and spanish tweets ."
"for each task , we provided training , development , and test datasets for english , arabic , and spanish tweets ."
"a 3-gram language model was trained from the target side of the training data for chinese and arabic , using the srilm toolkit ."
"a 5-gram language model with kneser-ney smoothing was trained with srilm on monolingual english data ."
"c . ~ = { ( subj , 0 ) , < n , 0 ) , < v , 0 ) , < comp , 0 ) , ( bar , 0 ) , and a type 1feature successor to the feature system and . . . < agr , 1 ) , < slash , 1 ) } ."
"we add a type 0 feature 0e ( with p ( 0e ) = { 0 } ) c. ~= { ( subj , 0 ) , < n , 0 ) , < v , 0 ) , < comp,0 ) , ( bar , 0 ) , and a type 1feature successor to the feature system and ... < agr , 1 ) , < slash , 1 ) } use this to build the set of indices ."
"shared task is a new approach to time normalization based on the semantically compositional annotation of time expressions ."
"the parsing time normalization task is the first effort to extend time normalization to richer and more complex time expressions ."
"we derive 100-dimensional word vectors using word2vec skip-gram model trained over the domain corpus ."
"we use the word2vec cbow model with a window size of 5 and a minimum frequency of 5 to generate 200-dimensional vectors ."
"syntactic language models can become intolerantly slow to train ."
"in contrast , syntactic language models can be much slower to train due to rich features ."
"the learning rule was adam with default tensorflow parameters ."
"the learning rule was adam with standard parameters ."
"we embed all words and characters into low-dimensional real-value vectors which can be learned by language model ."
"we derive 100-dimensional word vectors using word2vec skip-gram model trained over the domain corpus ."
"semantic knowledge ( e . g . word-senses ) has been defined at the ibm scientific center ."
"semantic knowledge is represented in a very detailed form ( word_sense pragmatics ) ."
"we used the target side of the parallel corpus and the srilm toolkit to train a 5-gram language model ."
"we use sri language model toolkit to train a 5-gram model with modified kneser-ney smoothing on the target-side training corpus ."
"to obtain this , we used mcut proposed by ding et al which is a type of spectral clustering ."
"to obtain this , we perform min-max cut proposed by ding et al , which is a spectral clustering method ."
"part-of-speech tagging is a crucial preliminary process in many natural language processing applications ."
"part-of-speech tagging is a key process for various tasks such as ` information extraction , text-to-speech synthesis , word sense disambiguation and machine translation ."
"information extraction ( ie ) is a main nlp aspects for analyzing scientific papers , which includes named entity recognition ( ner ) and relation extraction ( re ) ."
"information extraction ( ie ) is the process of finding relevant entities and their relationships within textual documents ."
"all systems are evaluated using case-insensitive bleu ."
"we adopted the case-insensitive bleu-4 as the evaluation metric ."
"automatic image captioning is a fundamental task that couples visual and linguistic learning ."
"automatic image captioning is a much studied topic in both the natural language processing ( nlp ) and computer vision ( cv ) areas of research ."
"in particular , the recent shared tasks of conll 2008 tackled joint parsing of syntactic and semantic dependencies ."
"the recent conll shared tasks have been focusing on semantic dependency parsing along with the traditional syntactic dependency parsing ."
"conditional random fields are undirected graphical models trained to maximize the conditional probability of the desired outputs given the corresponding inputs ."
"conditional random fields are discriminatively-trained undirected graphical models that find the globally optimal labeling for a given configuration of random variables ."
"additionally , a back-off 2-gram model with goodturing discounting and no lexical classes was built from the same training data , using the srilm toolkit ."
"a 5-gram language model was created with the sri language modeling toolkit and trained using the gigaword corpus and english sentences from the parallel data ."
"johnson and charniak proposed a tag-based noisy channel model , which showed great improvement over a boosting-based classifier ."
"johnson and charniak , 2004 ) proposed a tag-based noisy channel model for disfluency detection ."
"this is also in line with what has been previously observed in that a person may express the same stance towards a target by using negative or positive language ."
"as previously reported in , a person may express the same stance towards a target by using negative or positive language ."
"relation extraction ( re ) is a task of identifying typed relations between known entity mentions in a sentence ."
"relation extraction is a fundamental task in information extraction ."
"semantic difference is a ternary relation between two concepts ( apple , banana ) and a discriminative attribute ( red ) that characterizes the first concept but not the other ."
"semantic difference is a ternary relation between two concepts ( apple , banana ) and a discriminative feature ( red ) that characterizes the first concept but not the other ."
"ding and palmer propose a syntax-based translation model based on a probabilistic synchronous dependency insert grammar , a version of synchronous grammars defined on dependency trees ."
"ding and palmer introduce the notion of a synchronous dependency insertion grammar as a tree substitution grammar defined on dependency trees ."
"sentiment classification is a very domain-specific problem ; training a classifier using the data from one domain may fail when testing against data from another ."
"sentiment classification is a task to predict a sentiment label , such as positive/negative , for a given text and has been applied to many domains such as movie/product reviews , customer surveys , news comments , and social media ."
"bansal et al show the benefits of such modified-context embeddings in dependency parsing task ."
"bansal et al show that deps context is preferable to linear context on parsing task ."
"they have been useful as features in many nlp tasks ."
"others have found them useful in parsing and other tasks ."
"for example , faruqui and dyer use canonical component analysis to align the two embedding spaces ."
"more concretely , faruqui and dyer use canonical correlation analysis to project the word embeddings in both languages to a shared vector space ."
"the log-lineal combination weights were optimized using mert ."
"the minimum error rate training was used to tune the feature weights ."
"we train a secondorder crf model using marmot , an efficient higher-order crf implementation ."
"we model the sequence of morphological tags using marmot , a pruned higher-order crf ."
"word alignment is the process of identifying wordto-word links between parallel sentences ."
"word alignment is a fundamental problem in statistical machine translation ."
"sentiment analysis is a natural language processing ( nlp ) task ( cite-p-10-3-0 ) which aims at classifying documents according to the opinion expressed about a given subject ( federici and dragoni , 2016a , b ) ."
"sentiment analysis is a much-researched area that deals with identification of positive , negative and neutral opinions in text ."
"we use pre-trained glove embeddings to represent the words ."
"we use pre-trained vectors from glove for word-level embeddings ."
"so in most cases of irony , such features will be useful for detection ."
"given much of the irony in tweets is sarcasm , looking at some of these features may be useful ."
"that considers a word type and its allowed pos tags as a primary element of the model ."
"in this work , we take a more direct approach and treat a word type and its allowed pos tags as a primary element of the model ."
"we use wordsim-353 , which contains 353 english word pairs with human similarity ratings ."
"specifically , we used wordsim353 , a benchmark dataset , consisting of relatedness judgments for 353 word pairs ."
"mccarthy instead compares two semantic profiles in wordnet that contain the concepts corresponding to the nouns from the two argument positions ."
"in contrast to comparing head nouns directly , mccarthy instead compares the selectional preferences for each of the two slots ."
"the 50-dimensional pre-trained word embeddings are provided by glove , which are fixed during our model training ."
"we use the glove pre-trained word embeddings for the vectors of the content words ."
"mann and yarowsky use semantic information that is extracted from documents to inform a hierarchical agglomerative clustering algorithm ."
"mann and yarowsky used semantic information extracted from documents referring to the target person in an hierarchical agglomerative clustering algorithm ."
"twitter is a very popular micro blogging site ."
"twitter is a well-known social network service that allows users to post short 140 character status update which is called “ tweet ” ."
"the feature weights are tuned to optimize bleu using the minimum error rate training algorithm ."
"the parameter weights are optimized with minimum error rate training ."
"in this paper , we propose a forest-based tree sequence to string model , which is designed to integrate the strengths of the forest-based and the tree ."
"to integrate their strengths , in this paper , we propose a forest-based tree sequence to string translation model ."
"transliteration is a subtask in ne translation , which translates nes based on the phonetic similarity ."
"transliteration is often defined as phonetic translation ( cite-p-21-3-2 ) ."
"in this paper , we discuss methods for automatically creating models of dialog structure ."
"in future work , we will assess the performance of dialog structure prediction on recognized speech ."
"as a statistical significance test , we used bootstrap resampling ."
"we used bleu as our evaluation criteria and the bootstrapping method for significance testing ."
"we use the sri language model toolkit to train a 5-gram model with modified kneser-ney smoothing on the target-side training corpus ."
"we have used the srilm with kneser-ney smoothing for training a language model for the first stage of decoding ."
"the words in the document , question and answer are represented using pre-trained word embeddings ."
"the word embeddings are identified using the standard glove representations ."
"relation extraction is the task of detecting and classifying relationships between two entities from text ."
"relation extraction is a fundamental task in information extraction ."
"kobayashi et al identified opinion relations by searching for useful syntactic contextual clues ."
"kobayashi et al adopted a supervised learning technique to search for useful syntactic patterns as contextual clues ."
"neural models have shown great success on a variety of tasks , including machine translation , image caption generation , and language modeling ."
"various models for learning word embeddings have been proposed , including neural net language models and spectral models ."
"morphological disambiguation is the process of assigning one set of morphological features to each individual word in a text ."
"morphological disambiguation is the task of selecting the correct morphological parse for a given word in a given context ."
"case-insensitive bleu4 was used as the evaluation metric ."
"all systems are evaluated using case-insensitive bleu ."
"evaluation results show that our model clearly outperforms a number of baseline models in terms of both clustering posts ."
"the results show that our model can clearly outperform the baselines in terms of three evaluation metrics ."
"modified kneser-ney trigram models are trained using srilm upon the chinese portion of the training data ."
"gram language models are trained over the target-side of the training data , using srilm with modified kneser-ney discounting ."
"there are techniques for analyzing agreement when annotations involve segment boundaries , but our focus in this article is on words ."
"there are techniques for analyzing agreement when annotations involve segment boundaries , but our focus in this paper is on words ."
"for the tree-based system , we applied a 4-gram language model with kneserney smoothing using srilm toolkit trained on the whole monolingual corpus ."
"further , we apply a 4-gram language model trained with the srilm toolkit on the target side of the training corpus ."
"to reduce overfitting , we apply the dropout method to regularize our model ."
"to mitigate overfitting , we apply the dropout method to the inputs and outputs of the network ."
"we train a kn-smoothed 5-gram language model on the target side of the parallel training data with srilm ."
"for language model , we use a trigram language model trained with the srilm toolkit on the english side of the training corpus ."
"twitter is the medium where people post real time messages to discuss on the different topics , and express their sentiments ."
"twitter is a rich resource for information about everyday events – people post their tweets to twitter publicly in real-time as they conduct their activities throughout the day , resulting in a significant amount of mundane information about common events ."
"the neural embeddings were created using the word2vec software 3 accompanying ."
"those models were trained using word2vec skip-gram and cbow ."
"in this paper , we investigate unsupervised learning of field segmentation models ."
"in this work , we have examined the task of learning field segmentation models using unsupervised learning ."
"neural machine translation is currently the state-of-the art paradigm for machine translation ."
"neural machine translation has recently become the dominant approach to machine translation ."
"we use srilm toolkit to build a 5-gram language model with modified kneser-ney smoothing ."
"these language models were built up to an order of 5 with kneser-ney smoothing using the srilm toolkit ."
"the constituent context model for inducing constituency parses was the first unsupervised approach to surpass a right-branching baseline ."
"the constituent-context model is the first unsupervised constituency grammar induction system that achieves better performance than the trivial right branching baseline for english ."
"in this paper , we propose a procedure to train multi-domain , recurrent neural network-based ( rnn ) language generators via multiple adaptation ."
"the paper presents an incremental recipe for training multi-domain language generators based on a purely data-driven , rnn-based generation model ."
"we use pre-trained word2vec word vectors and vector representations by tilk et al to obtain word-level similarity information ."
"we also used word2vec to generate dense word vectors for all word types in our learning corpus ."
"the stochastic gradient descent with back-propagation is performed using adadelta update rule ."
"training is done through stochastic gradient descent over shuffled mini-batches with adadelta update rule ."
"in the n-coalescent , every pair of lineages merges independently with rate 1 , with parents chosen uniformly at random from the set of possible parents ."
"in the n-coalescent , every pair of lineages merges independently with rate 1 , with parents chosen uniformly at random from the set of possible parents at the previous time step ."
"in our approach is to allow highly flexible reordering operations , in combination with a discriminative model that can condition on rich features of the source-language input ."
"a critical difference in our work is to allow arbitrary reorderings of the source language sentence ( as in phrase-based systems ) , through the use of flexible parsing operations ."
"we measure the translation quality using a single reference bleu ."
"we evaluated the translation quality of the system using the bleu metric ."
"we use srilm toolkit to build a 5-gram language model with modified kneser-ney smoothing ."
"a trigram language model with modified kneser-ney discounting and interpolation was used as produced by the srilm toolkit ."
"sentence compression is a standard nlp task where the goal is to generate a shorter paraphrase of a sentence ."
"sentence compression is the task of compressing long , verbose sentences into short , concise ones ."
"wu presents a better-constrained grammar designed to only produce tail-recursive parses ."
"wu proposes a bilingual segmentation grammar extending the terminal rules by including phrase pairs ."
"although coreference resolution is a subproblem of natural language understanding , coreference resolution evaluation metrics have predominately been discussed in terms of abstract entities and hypothetical system errors ."
"coreference resolution is the process of determining whether two expressions in natural language refer to the same entity in the world ."
"we trained a tri-gram hindi word language model with the srilm tool ."
"we used the srilm toolkit to generate the scores with no smoothing ."
"sentiment analysis is a research area where does a computational analysis of people ’ s feelings or beliefs expressed in texts such as emotions , opinions , attitudes , appraisals , etc . ( cite-p-12-1-3 ) ."
"sentiment analysis is the task of automatically identifying the valence or polarity of a piece of text ."
"we adopt two standard metrics rouge and bleu for evaluation ."
"for the evaluation of the results we use the bleu score ."
"in this paper , we focus on designing a review generation model that is able to leverage both user and item information ."
"in this paper , we focus on the problem of building assistive systems that can help users to write reviews ."
"the syntactic feature set is extracted after dependency parsing using the maltparser ."
"all data is automatically annotated with syntactic tags using maltparser ."
"we used a bitext projection technique to transfer dependency-based opinion frames ."
"we propose a cross-lingual framework for fine-grained opinion mining using bitext projection ."
"knowledge of our native language provides an initial foundation for second language learning ."
"our native language ( l1 ) plays an essential role in the process of lexical choice ."
"semantic roles are approximated by propbank argument roles ."
"direction , manner , and purpose are propbank adjunctive argument labels ."
"in this paper , we study the problem of sentiment analysis on product reviews ."
"in this paper , we propose a novel and effective approach to sentiment analysis on product reviews ."
"in this paper we present an algorithmic framework which allows an automated acquisition of map-like information from the web , based on surface patterns ."
"in this paper we utilize a pattern-based lexical acquisition framework for the discovery of geographical information ."
"circles denote events , squares denote arguments , solid arrows represent event-event relations , and dashed arrows represent event-argument relations ."
"the circles denote fixations , and the lines are saccades ."
"semantic parsing is the task of mapping natural language sentences to a formal representation of meaning ."
"semantic parsing is the task of translating natural language utterances into a machine-interpretable meaning representation ."
"each context consists of approximately a paragraph of surrounding text , where the word to be discriminated ( the target word ) is found approximately in the middle of the context ."
"1 a context consists of all the patterns of n-grams within a certain window around the corresponding entity mention ."
"we used the pre-trained google embedding to initialize the word embedding matrix ."
"in this baseline , we applied the word embedding trained by skipgram on wiki2014 ."
"the word embeddings used in each neural network is initialized with the pre-trained glove with the dimension of 300 ."
"the word embeddings are initialized using the pre-trained glove , and the embedding size is 300 ."
"in spite of this broad attention , the open ie task definition has been lacking ."
"in spite of this wide attention , open ie ’ s formal definition is lacking ."
"neural network models have been exploited to learn dense feature representation for a variety of nlp tasks ."
"interestingly convolutional neural networks , widely used for image processing , have recently emerged as a strong class of models for nlp tasks ."
"reordering is a difficult task in translating between widely different languages such as japanese and english ."
"reordering is a common problem observed in language pairs of distant language origins ."
"we initialize our word vectors with 300-dimensional word2vec word embeddings ."
"our cdsm feature is based on word vectors derived using a skip-gram model ."
"we define a conditional random field for this task ."
"our model is a first order linear chain conditional random field ."
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Reformatted version of the ParaSCI dataset from ParaSCI: A Large Scientific Paraphrase Dataset for Longer Paraphrase Generation. Data retrieved from dqxiu/ParaSCI.

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