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the frequent frame you it , for example , largely identifies verbs , as shown in , taken from child-directed speech in the childes database---the frequent frame you it , for example , largely identifies verbs , as shown in , taken from the childes database of child-directed speech | 1 |
a substantial increase in performance is achieved , according to several standard mt evaluation metrics---in this paper we present a fully unsupervised word sense disambiguation method that requires only a dictionary and unannotated text | 0 |
evaluation is done using the bleu metric with four references---but it also eliminates the need to directly predict the direction of translation of the parallel corpus | 0 |
to avoid this problem we use the concept of class proposed for a word n-gram model---this can be regarded as the clustering criterion usually used in a class-based n-gram language model | 1 |
in a distributional similarity-based model for selectional preferences is introduced , reminiscent of that of pantel and lin---erk introduced a distributional similarity-based model for selectional preferences , reminiscent of that of pantel and lin | 1 |
coreference resolution is the task of clustering a sequence of textual entity mentions into a set of maximal non-overlapping clusters , such that mentions in a cluster refer to the same discourse entity---coreference resolution is a key problem in natural language understanding that still escapes reliable solutions | 1 |
coreference resolution is the task of determining when two textual mentions name the same individual---we used the liblinear-java library 2 with the l2-regularized logistic regression method for both trigger detection and edge detection | 0 |
in sum , our study shows that textual entailment can profit substantially from better discourse handling---instances , we argue that discourse references have the potential of substantially improving textual entailment | 1 |
sentence compression is a standard nlp task where the goal is to generate a shorter paraphrase of a sentence---word alignment is a fundamental problem in statistical machine translation | 0 |
the pattern-matching approach proposed by johnson ( 2002 ) for a similar task for phrase structure trees is extended with machine learning techniques---we developed a similar approach using dependency structures rather than phrase structure trees , which , moreover , extends bare pattern matching with machine learning techniques | 1 |
more recently , neural networks have become prominent in word representation learning---deep neural networks have gained recognition as leading feature extraction methods for word representation | 1 |
since discourse is a natural form of communication , it favors the observation of the patient ’ s functionality in everyday life---we used the srilm toolkit to build unpruned 5-gram models using interpolated modified kneser-ney smoothing | 0 |
coreference resolution is the task of partitioning the set of mentions of discourse referents in a text into classes ( or ‘ chains ’ ) corresponding to those referents ( cite-p-12-3-14 )---the general sentiment information extracted from sentiment lexicons is adapted to target domain using domain-specific sentiment | 0 |
we measured performance using the bleu score , which estimates the accuracy of translation output with respect to a reference translation---we measured the overall translation quality with the help of 4-gram bleu , which was computed on tokenized and lowercased data for both systems | 1 |
the challenge here is to deterministically choose a shift or reduce action---we use srilm toolkit to train a trigram language model with modified kneser-ney smoothing on the target side of training corpus | 0 |
the ims corpus workbench includes both a query engine and a motif-based user visualisation tool---in pcfg-las , first introduced by matsuzaki et al , the refined categories are learnt from the treebank using unsupervised techniques | 0 |
the proposed word embeddings show improvements in sentiment classification , while maintaining their performance on subjectivity and topic classifications---in section 6 , the proposed word embeddings show evident improvements on sentiment classification , as compared to the base model | 1 |
to capture the relation between words , kalchbrenner et al propose a novel cnn model with a dynamic k-max pooling---kalchbrenner et al introduced a convolutional neural network for sentence modeling that uses dynamic k-max pooling to better model inputs of varying sizes | 1 |
we use the stanford parser with stanford dependencies---we use the stanford parser to extract a set of dependencies from each comment | 1 |
planas and furuse propose approaches that use lemma and parts of speech along with surface form comparison---both planas and furuse and hodasz and pohl proposed to use lemma and parts of speech along with surface form comparison | 1 |
we use the moses smt framework and the standard phrase-based mt feature set , including phrase and lexical translation probabilities and a lexicalized reordering model---we use a fourgram language model with modified kneser-ney smoothing as implemented in the srilm toolkit | 0 |
the spanish experiments transfer from english to spanish using the spanish portion of the europarl corpus---all experiments used the europarl parallel corpus as sources of text in the languages of interest | 1 |
in this paper we consider several estimation methods for probabilistic context-free grammars , and we show that the resulting grammars have the consistency property---pang et al conducted early polarity classification of reviews using supervised approaches | 0 |
the nse memory update is scalable and potentially more robust to train---nse is flexible , robust and suitable for practical nlu tasks and can be trained easily | 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 determining which mentions in a text are used to refer to the same real-world entity | 1 |
here we adapt the partial tree kernel proposed by moschitti 3 , which can be used with both constituent and dependency parse trees---we use the partial tree kernel to measure the similarity between two trees , since it is suitable for dependency parsing | 1 |
we use the sri language model toolkit to train a 5-gram model with modified kneser-ney smoothing on the target-side training corpus---for the language model we use the corpus of 60,000 simple english wikipedia articles 3 and build a 3-gram language model with kneser-ney smoothing trained with srilm | 1 |
shen et al proposed a target dependency language model for smt to employ target-side structured information---shen et al propose the well-formed dependency structure to filter the hierarchical rule table | 1 |
sentiment analysis is the computational analysis of people ’ s feelings or beliefs expressed in texts such as emotions , opinions , attitudes , appraisals , etc . ( cite-p-11-3-3 )---sentiment analysis is a natural language processing ( nlp ) task ( cite-p-10-1-14 ) which aims at classifying documents according to the opinion expressed about a given subject ( federici and dragoni , 2016a , b ) | 1 |
we follow the approach of schwenk and koehn and trained domain-specific language models separately and then linearly interpolated them using srilm with weights optimized on the heldout dev-set---we followed the approach of schwenk and koehn by training language models from each sub-corpus separately and then linearly interpolated them using srilm with weights optimized on the held-out dev-set | 1 |
the concept of graph degeneracy was introduced by with the k-core decomposition technique and was first applied to the study of cohesion in social networks---the concept of graph degeneracy was introduced by and first applied to the study of cohesion in social networks | 1 |
the 5-gram kneser-ney smoothed language models were trained by srilm , with kenlm used at runtime---the srilm toolkit was used to build the trigram mkn smoothed language model | 1 |
we compare our graphbtm approach with the avitm and the lda model---we briefly describe lda model as used in our qa system | 1 |
motivated by this limitation , the study aims to investigate the use of content features in speech scoring systems---this study focuses on representing content of speech transcripts to facilitate automatic scoring of speech | 1 |
for example , shen and lapata show the potential improvement that framenet can bring on the performance of a question answering system---shen and lapata , show that the use of framenet can potentially improve the performance of question answering systems | 1 |
in the above examples , classifier “ hiki ” is used to count noun “ inu ( dog ) ” , while “ satsu ” for “ hon ( book ) ”---word sense disambiguation ( wsd ) is a natural language processing ( nlp ) task in which the correct meaning ( sense ) of a word in a given context is to be determined | 0 |
the smt system was tuned on the development set newstest10 with minimum error rate training using the bleu error rate measure as the optimization criterion---the weights 位 m in the log-linear model were trained using minimum error rate training with the news 2009 development set | 1 |
we use the system combination framework of heafield and lavie , which has an open-source implementation---we use an open source memt implementation by heafield and lavie to combine the outputs of our systems | 1 |
one of the clear successes in computational modeling of linguistic patterns has been that of finite state transducer models for morphological analysis and generation---one of the clear successes in computational modeling of linguistic patterns has been finite state transducer models for morphological analysis and generation | 1 |
twitter is a widely used microblogging environment which serves as a medium to share opinions on various events and products---we used moses , a phrase-based smt toolkit , for training the translation model | 0 |
lexical analogies occur frequently in text and are useful in various natural language processing tasks---lexical analogies also have applications in word sense disambiguation , information extraction , question-answering , and semantic relation classification | 1 |
we used the penn treebank wsj corpus to perform empirical experiments on the proposed parsing models---we trained the c-structure pruning algorithm on the standard sections of penn treebank wall street journal text | 1 |
this study has experimentally investigated the impact of contextual information selection , by extracting three kinds of word relationships from corpora : dependency , sentence co-occurrence , and proximity---in this study , we experimentally investigated the impact of contextual information selection , by extracting three kinds of contextual information — dependency , sentence co-occurrence , and proximity | 1 |
all the weights are initialized with xavier initialization method---all weights are initialized by the xavier method | 1 |
moreover , al-sabbagh and girju introduce an approach to build a da-to-msa lexicon through mining the web---al-sabbagh and girju described an approach of mining the web to build a da-to-msa lexicon | 1 |
in this work , we integrate residual connections with our networks to form connections between layers---we further add skip connections between the lstm layers to the softmax layers , since they are proved effective for training neural networks | 1 |
the word vectors of vocabulary words are trained from a large corpus using the glove toolkit---the model parameters in word embedding are pretrained using glove | 1 |
adding subjectivity labels to wordnet could also support automatic subjectivity analysis---subjectivity feature can significantly improve the accuracy of a word sense disambiguation system | 1 |
in amr , the choice is made to attach polarity edges to the verb , which prohibits syntactic analysis of such constructions---syntactically attach to the verb in amr could be mitigated by a rule that allows for the movement of polarity edges | 1 |
brockett et al use smt to correct countability errors for a set of 14 mass nouns that pose problems to chinese esl learners---successful discriminative parsers have used generative models to reduce training time and raise accuracy above generative baselines | 0 |
we follow soon et al , ng and cardie and luo et al to generate most of the 29 features we use for the pairwise model---we follow soon et al and ng and cardie to generate most of our features for the pairwise model | 1 |
we apply sri language modeling toolkit to train a 4-gram language model with kneser-ney smoothing---we use srilm toolkit to build a 5-gram language model with modified kneser-ney smoothing | 1 |
we used the first-stage parser of charniak and johnson for english and bitpar for german---we used the first-stage pcfg parser of charniak and johnson for english and bitpar for german | 1 |
in this paper , we present smatch , a metric that calculates the degree of overlap between two semantic feature structures---in this work , we provide an evaluation metric that uses the degree of overlap between two whole-sentence semantic structures | 1 |
semantic parsing is the task of translating natural language utterances into a machine-interpretable meaning representation---components of the graph represent the different senses of the target word | 0 |
we use the wsj corpus , a pos annotated corpus , for this purpose---our neural model for ecd exceptionally boosts the state-of-the-art detection | 0 |
occam¡¯s razor is further implemented to this attention for better representation---our ner model is built according to conditional random fields methods , by which we convert the problem of ner into that of sequence labeling | 0 |
similar to the evaluation for traditional summarization tasks , we use the rouge metrics to automatically evaluate the quality of produced summaries given the goldstandard reference news---the 5-gram target language model was trained using kenlm | 0 |
we used the berkeley parser for our evaluation and trained with six iterations for latent annotations---for our experiments , we used the latent variablebased berkeley parser | 1 |
our baseline system is based on a hierarchical phrase-based translation model , which can formally be described as a synchronous context-free grammar---our translation system uses cdec , an implementation of the hierarchical phrasebased translation model that uses the kenlm library for language model inference | 1 |
named entity disambiguation ( ned ) is the task of determining which concrete person , place , event , etc . is referred to by a mention---although such approaches perform reasonably well , features are often derived from language-specific resources | 0 |
the dependency-based evaluation used in the experiments follows the method of lin and k眉bler and telljohann , converting the original treebank trees and the parser output into dependency relations of the form word pos head---the dependency-based evaluation used in the experiments follows the method of lin and k眉bler et al , converting the original treebank trees and the parser output into dependency relationships of the form word pos head | 1 |
coreference resolution is the task of determining whether two or more noun phrases refer to the same entity in a text---coreference resolution is the problem of identifying which noun phrases ( nps , or mentions ) refer to the same real-world entity in a text or dialogue | 1 |
we use 300d glove vectors trained on 840b tokens as the word embedding input to the lstm---snyder and barzilay combine an agreement model based on contrastive rst relations with a local aspect model | 0 |
firat et al proposed multi-way multilingual nmt using multiple encoders and decoders with a single shared attention mechanism---we adapted the moses phrase-based decoder to translate word lattices | 0 |
given a word-aligned sentence pair , a phrase decomposition tree can be extracted with a shift-reduce algorithm---following , we use the shift-reduce style algorithm to efficiently encode the word aligned phrase-pair as a normalized decomposition tree | 1 |
arabic is a morphologically rich language that is much more challenging to work , mainly due to its significantly larger vocabulary---arabic is a morphologically rich language , in which a word carries not only inflections but also clitics , such as pronouns , conjunctions , and prepositions | 1 |
to this effect , we use the attention mechanism developed originally for sequence-tosequence models , which has proven effective in machine translation luong et al , 2015 ) and da classification---similar to the dominant nmt model , we adopt the attention model luong et al , 2015 ) to calculate the weights , which indicate the alignment probability | 1 |
this is partly due to the annotation formats of treebanks such as the penn treebank , which are used as a data source for grammar extraction---the use of pcfg is tied to the annotation principles of popular treebanks , such as the penn treebank , which are used as a data source for grammar extraction | 1 |
we trained a 5-gram language model on the english side of each training corpus using the sri language modeling toolkit---we trained a 5-gram sri language model using the corpus supplied for this purpose by the shared task organizers | 1 |
we trained a 4-gram language model on this data with kneser-ney discounting using srilm---we used a 5-gram language model with modified kneser-ney smoothing , built with the srilm toolkit | 1 |
a 4-gram language model is trained on the xinhua portion of the gigaword corpus with the srilm toolkit---for the n-gram lm , we use srilm toolkits to train a 4-gram lm on the xinhua portion of the gigaword corpus | 1 |
our model modifies the attention based architecture proposed by bahdanau et al , and implements as a deep stack lstm framework---our nnape model is inspired by the mt work of bahdanau et al which is based on bidirectional recurrent neural networks | 1 |
relation extraction is the task of detecting and characterizing semantic relations between entities from free text---relation extraction is the task of predicting attributes and relations for entities in a sentence ( zelenko et al. , 2003 ; bunescu and mooney , 2005 ; guodong et al. , 2005 ) | 1 |
it is a common observation that domain specific wsd exhibits high level of accuracy even for the all-words scenario -provided training and testing are on the same domain---we use a maximum entropy classifier with a large number of boolean features , some of which are novel | 0 |
we use our reordering model for n-best re-ranking and optimize bleu using minimum error rate training---we substitute our language model and use mert to optimize the bleu score | 1 |
the europarl corpus is one of the main bitexts available , created from professional translations of parliamentary proceedings and covering the official eu languages---europarl is a parallel corpus of proceedings of the european parliament , currently available in 21 european languages , although not every sentence is translated into every language | 1 |
in this paper , we have proposed a novel approach for logically recognizing social constructs from textual conversations---in this paper , we use a mixture of logic-based and statistical approaches which better encodes the domain knowledge and infers higher-level constructs from indirect textual | 1 |
according to the experimental results , the classifiers incorporating target-dependent features significantly outperform the previous target-independent classifiers---according to the experimental results , machine learning based classifiers outperform the unsupervised approach , where the best performance is achieved by the svm classifier | 1 |
in this paper we proposed a new parsing algorithm based on a branch and bound framework---in this paper , we proposed an exact and efficient decoding algorithm based on the branch and bound ( b & b ) framework | 1 |
we use the stanford parser with stanford dependencies---we use the collapsed tree formalism of the stanford dependency parser | 1 |
coreference resolution is the process of linking multiple mentions that refer to the same entity---coreference resolution is the task of determining whether two or more noun phrases refer to the same entity in a text | 1 |
in the training data , we found that 50.98 % sentences labeled as ¡°should be extracted¡± belongs to the first 5 sentences , which may cause the trained model tends to select more leading sentences---in the training data , we found that 50 . 98 % sentences labeled as ¡° should be extracted ¡± belongs to the first 5 sentences , which may cause | 1 |
arthur et al and feng et al try to incorporate a translation lexicon into nmt in order to obtain the correct translation of low-frequency words---arthur et al introduced discrete translation lexicons into nmt to imrpove the translations of these low-frequency words | 1 |
we use the attention-based nmt model introduced by bahdanau et al as our text-only nmt baseline---for our experiments , we use a phrase-based translation system similar to moses | 0 |
the english corpus contains 47613 sentences , that were pos tagged using stepp tagger , and use the lemmatizer to extract and stem content words---the english corpus nhtsa was pos-tagged and stemmed with stepp tagger and dependency parsed using the mst parser | 1 |
we describe a number of key steps in obtaining this level of performance---we describe a number of key steps used to obtain this level of performance | 1 |
reisinger and mooney and huang et al also presented methods that learn multiple embeddings per word by clustering the contexts---in an attempt to capture the different senses or usage of a word , reisinger and mooney and huang et al proposed multi-prototype models for inducing multiple embeddings for each word | 1 |
for ner , we use a bengali news corpus , developed from the archive of a leading bengali newspaper available in the web---we evaluated the reordering approach within the moses phrase-based smt system | 0 |
kim et al use word representations constructed by cnn with recurrent neural network for language modeling---kim et al proposed a convolutional module to process complex inputs for the problem of language modeling | 1 |
we present a trainable model for identifying sentence boundaries in raw text---we have described an approach to identifying sentence boundaries | 1 |
semantic role labeling ( srl ) is a kind of shallow sentence-level semantic analysis and is becoming a hot task in natural language processing---semantic role labeling ( srl ) is the process of producing such a markup | 1 |
the formal semantic component of the system translates the disambiguated parse into a discourse representation structure---the itp nlu module parses one sentence , and maps its parse tree onto a discourse representation structure | 1 |
bleu is widely used for automatic evaluation of machine translation systems---bleu is a popular metric for evaluating statistical machine translation systems and fits our needs well | 1 |
we perform knowledge base inference using the path ranking algorithm---then we review the path ranking algorithm introduced by lao and cohen | 1 |
for building our ap e b2 system , we set a maximum phrase length of 7 for the translation model , and a 5-gram language model was trained using kenlm---to rerank the candidate texts , we used a 5-gram language model trained on the europarl corpus using kenlm | 1 |
word alignment is a fundamental problem in statistical machine translation---word alignment is the process of identifying wordto-word links between parallel sentences | 1 |
and for language modeling , we used kenlm to build a 5-gram language model---in this paper , we proposed multi-step stacked learning to extract n-gram features | 0 |
the model was built using the srilm toolkit with backoff and good-turing smoothing---the srilm toolkit was used to build this language model | 1 |
we train a 4-gram language model on the xinhua portion of the english gigaword corpus using the srilm toolkits with modified kneser-ney smoothing---we train an english language model on the whole training set using the srilm toolkit and train mt models mainly on a 10k sentence pair subset of the acl training set | 1 |
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