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therefore , the main extension towards a comprehensive model of the acquisition of allophonic rules would be to include acoustic indicators---the latent dirichlet allocation is the most basic topic model , which generates each word in a document based on a unigram word distribution defined by a topic allocated to that word | 0 |
relation extraction is the task of detecting and classifying relationships between two entities from text---our models measure cross-lingual similarity of the coreference chains to make clustering decisions | 0 |
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 5-gram language model with the xinhua portion of english gigaword corpus and the english side of the training set using the srilm toolkit | 1 |
for improving the word alignment , we use the word-classes that are trained from a monolingual corpus using the srilm toolkit---for the tree-based system , we applied a 4-gram language model with kneserney smoothing using srilm toolkit trained on the whole monolingual corpus | 1 |
we use binary crossentropy loss and the adam optimizer for training the nil-detection models---we considered one layer and used the adam optimizer for parameter optimization | 1 |
thus , event extraction is a difficult task and requires substantial training data---event extraction is a particularly challenging problem in information extraction | 1 |
long short-term memory units are modified recurrent units that can cope with the problem of vanishing gradients more effectively---long short-term memory units are the modified recurrent units which are proposed to handle the problem of vanishing gradients effectively | 1 |
in this paper , drawing intuitions from the turing test , we propose using an adversarial training approach for response generation---in this paper , drawing intuition from the turing test , we propose using adversarial training for open-domain dialogue generation | 1 |
this score is used , for instance , in the collocation compiler xtract and in the lexicon extraction system champollion---it has been used before in the collocation compiler xtract and in the lexicon extraction system champollion | 1 |
in this paper we use a simple unlexicalized dependency model due to klein and manning---we use the deterministic harmonic initializer from klein and manning | 1 |
the reports of the shared task in news 2009 and news 2010 , li et al , 2010 highlighted two particularly popular approaches for transliteration generation among the participating systems---that , with an appropriate heuristic , our algorithm can extract k-best lists in a fraction of the time required by current approaches to k-best extraction | 0 |
most existing approaches tackle argumentation mining in a supervised manner trained on manually annotated documents from a specific domain---however , most existing argumentation mining approaches tackle the classification of argumentativeness only for a few manually annotated documents | 1 |
a 4-gram language model is trained on the xinhua portion of the gigaword corpus with the srilm toolkit---the language model is trained on the target side of the parallel training corpus using srilm | 1 |
srilm toolkit was used to create up to 5-gram language models using the mentioned resources---a 4-gram language model was trained on the target side of the parallel data using the srilm toolkit | 1 |
stance detection is a difficult task since it often requires reasoning in order to determine whether an utterance is in favor of or against a specific issue---sentiment classification has advanced considerably since the work | 0 |
verbnet has long been used in nlp for semantic role labeling and other inference-enabling tasks---verbnet has been successfully used to support semantic role labeling , information extraction and semantic parsing | 1 |
as a stateof-the-art clustering method , we consider brown clustering as implemented in the srilm-toolkit---in order to cluster lexical items , we use the algorithm proposed by brown et al , as implemented in the srilm toolkit | 1 |
moreover , xing et al incorporated topic words into seq2seq frameworks , where topic words are obtained from a pre-trained l-da model---xing et al pre-defined a set of topics from an external corpus to guide the generation of the seq2seq model | 1 |
we will refer to such systems as monolingual syntax-based systems---using definition-based conceptual co-occurrence data collected from a relatively small corpus , our sense disambiguation system has achieved accuracy comparable to human performance given the same amount of contextual information | 0 |
finkel and manning propose a discriminative parsingbased method for nested named entity recognition , employing crfs as its core---finkel and manning propose a crf-based constituency parser which takes each named entity as a constituent in the parsing tree | 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---we train trigram language models on the training set using the sri language modeling tookit | 1 |
this taxonomy is augmented with various meta information related to each node as mentioned above---the automatically generated taxonomy and the agent can get relevant information associated with different nodes | 1 |
it has recently been shown that different nlp models can be effectively combined using dual decomposition---have shown that dual decomposition or lagrangian relaxation is an elegant framework for combining different types of nlp tasks | 1 |
we used moses with the default configuration for phrase-based translation---for phrase-based smt translation , we used the moses decoder and its support training scripts | 1 |
zelenko et al , 2003 ) showed how to extract relations by computing the kernel functions between the kernels of shallow parse trees---in this paper , we use this intuition to define a joint inference model that captures the interdependencies between verb | 0 |
such constraints are known to introduce inconsistencies in probabilistic models estimated using simple relative frequency---such constraints are known to introduce inconsistencies in probabilistic models estimated using simple relative frequency , as discussed in abney | 1 |
multiword expressions are defined as idiosyncratic interpretations that cross word boundaries or spaces---multiword expressions or mwes can be understood as idiosyncratic interpretations or words with spaces wherein concepts cross the word boundaries or spaces | 1 |
for example , tree kernel , one of the convolution kernels , implicitly maps the instance represented in a tree into all-subtrees space---tree kernel implicitly maps the example represented in a labeled ordered tree into all subtree spaces , and tree kernel can consider the frequency of subtrees | 1 |
neural abstractive summarization models have led to promising results in summarizing relatively short documents---summarization models have led to promising results in summarizing relatively short documents | 1 |
unfortunately , wordnet is a fine-grained resource , encoding sense distinctions that are often difficult to recognize even for human annotators ( cite-p-15-1-6 )---the translation quality is evaluated by case-insensitive bleu and ter metrics using multeval | 0 |
kohama et al improved the work of shibata and kurohashi by utilizing crowdsourced data for shared argument learning---shibata and kurohashi proposed a twostage approach for japanese event relation knowledge acquisition | 1 |
in this paper we have presented a novel framework for unsupervised role induction---in this paper we describe an unsupervised approach to argument classification or role induction | 1 |
in recent years , some other related researchers have proposed the tasks of high-quality question generation and generating questions from queries---when used as the underlying input representation , word vectors have been shown to boost the performance in nlp tasks | 0 |
we first trained a trigram bnlm as the baseline with interpolated kneser-ney smoothing , using srilm toolkit---following labeling , negated tokens are assigned to their respective cues | 0 |
if n -- ~ 0 , the clause is a unit clause and is written simply as p---a clause is a finite set of atomic constraint denoting their conjunction | 1 |
we use 300 dimension word2vec word embeddings for the experiments---we use the word2vec tool to pre-train the word embeddings | 1 |
we use the skip-gram model , trained to predict context tags for each word---we pre-train the word embedding via word2vec on the whole dataset | 1 |
word alignment is a central problem in statistical machine translation ( smt )---word alignment is a key component of most endto-end statistical machine translation systems | 1 |
we measured inter-judge agreement on the likert-scale annotations using their intraclass correlation---we measured inter-judge agreement by means of their intraclass correlation | 1 |
experiments on translation from german to english show a 0.5 % improvement in bleu score over a phrase-based system---luo et al use bell trees to represent the search space of the coreference resolution problem | 0 |
for closed track , we implement the baseline system using the stanford parser with default parameters for performance comparison---we use the stanford parser to generate the grammar structure of review sentences for extracting syntactic d-features | 1 |
the performance of the phrase-based smt system is measured by bleu score and ter---translation performance is measured using the automatic bleu metric , on one reference translation | 1 |
the un-pre-marked japanese corpus is used to train a language model using kenlm---the 5-gram target language model was trained using kenlm | 1 |
we use sri language model toolkit to train a 5-gram model with modified kneser-ney smoothing on the target-side training corpus---the process of identifying the correct meaning , or sense of a word in context , is known as word sense disambiguation ( wsd ) | 0 |
in this paper , we describe easyenglish , a tool that helps writers produce clearer and simpler english by pointing out ambiguity and complexity---in this paper , we describe easyenglish , a tool that helps writers produce clearer and simpler english | 1 |
entity linking ( el ) is the task of disambiguating mentions in text by associating them with entries in a predefined database of mentions ( persons , organizations , etc )---inversion transduction grammar , or itg , is a wellstudied synchronous grammar formalism | 0 |
the phrase-based translation systems rely on language model and lexicalized reordering model to capture lexical dependencies that span phrase boundaries---extraction set models allow us to incorporate the same phrasal relative frequency statistics that drive phrase-based translation performance | 1 |
more importantly , chinese is a language that lacks the morphological clues that help determine the pos tag of a word---chinese is a language without natural word delimiters | 1 |
sarcasm is a form of verbal irony that is intended to express contempt or ridicule---sarcasm is a sophisticated speech act which commonly manifests on social communities such as twitter and reddit | 1 |
we first train a word2vec model on fr-wikipedia 11 to obtain non contextual word vectors---we estimated 5-gram language models using the sri toolkit with modified kneser-ney smoothing | 0 |
we compute the interannotator agreement in terms of the bleu score---we measure the translation quality using a single reference bleu | 1 |
finally , the articles are parsed with the cdg dependency parser---the weights for the loglinear model are learned using the mert system | 0 |
however , if cluster labeling is possible , we can use many techniques in the ensemble learning---for large datasets , we use an ensemble technique inspired by bagging | 1 |
stance detection is a difficult task since it often requires reasoning in order to determine whether an utterance is in favor of or against a specific issue---stance detection is the task of estimating whether the attitude expressed in a text towards a given topic is ‘ in favour ’ , ‘ against ’ , or ‘ neutral ’ | 1 |
coreference resolution is the task of determining which mentions in a text refer to the same entity---coreference resolution is the process of linking multiple mentions that refer to the same entity | 1 |
as a feature-based method , we use the structural correspondence learning---finally , we compare against structural correspondence learning , another feature learning algorithm | 1 |
among them , we examined for the first time an approach based on distinctive-collexeme analysis---among them , we examine for the first time a low-resource approach based on distinctive-collexeme analysis | 1 |
automatic image captioning is a much studied topic in both the natural language processing ( nlp ) and computer vision ( cv ) areas of research---automatic image captioning is a fundamental task that couples visual and linguistic learning | 1 |
word sense disambiguation ( wsd ) is a key task in computational lexical semantics , inasmuch as it addresses the lexical ambiguity of text by making explicit the meaning of words occurring in a given context ( cite-p-18-3-10 )---word sense disambiguation ( wsd ) is a problem of finding the relevant clues in a surrounding context | 1 |
for the semantic language model , we used the srilm package and trained a tri-gram language model with the default goodturing smoothing---we used the srilm toolkit to simulate the behavior of flexgram models by using count files as input | 1 |
we can use an automatic evaluation measure such as bleu as ev---in this demonstration , we present t he p rojector , an interactive gui designed to assist researchers in such analysis : it allows users to execute and visually inspect annotation projection | 0 |
framenet is an expert-built lexical-semantic resource incorporating the theory of frame-semantics---an argument usually consists of a claim ( also known as conclusion ) and some premises ( also known as evidences ) offered in support of the claim | 0 |
we use the automatic mt evaluation metrics bleu , meteor , and ter , to evaluate the absolute translation quality obtained---we use two standard evaluation metrics bleu and ter , for comparing translation quality of various systems | 1 |
to train the link embeddings , we use the speedy , skip-gram neural language model of mikolov et al via their toolkit word2vec---we use the pre-trained word2vec embeddings provided by mikolov et al as model input | 1 |
it is a collection of the most common character-based n-grams used as a language profile---it is a ranked collection of the most common character-based n-grams for each language used as its profile | 1 |
using probability distributions over verb subcategorisation frames , we obtained an intuitively plausible clustering of 57 verbs into 14 classes---probability distributions over verb subcategorisation frames , we obtained an intuitively plausible clustering of 57 verbs into 14 classes | 1 |
richman and schone use article classification knowledge from english wikipedia to produce ne-annotated corpora in other languages---richman et al utilize multilingual characteristics of wikipedia to annotate a large corpus of text with named entity tags | 1 |
the baseline further contains a hierarchical reordering model and a 7-gram word class language model---the baseline system includes moses baseline feature functions , plus eight hierarchical lexicalized reordering model feature functions | 1 |
we computed pre-trained word embeddings in 300 dimensions for all the words in the stories using the skip-gram architecture algorithm---we used all post bodies in the unlabeled dataset to train a skip-gram model of 50 dimensions | 1 |
relation extraction ( re ) has been defined as the task of identifying a given set of semantic binary relations in 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 |
we use the edinburgh twitter corpus as the background corpus for frequency calculation , and a dictionary containing 82,324 words---we use the edinburgh twitter corpus for data collection , which contains 97 million twitter messages | 1 |
a 4-gram language model is trained on the monolingual data by srilm toolkit---the language models are 4-grams with modified kneser-ney smoothing which have been trained with the srilm toolkit | 1 |
mcdonald and pereira use graph-based algorithms for dag parsing simply using approximate interference in an edge-factored dependency model starting from dependency trees---the approach proposed by sasano et al aims to develop heuristics to flexibly search by using a simple , manually created derivational rule | 0 |
the feature weights are tuned with minimum error-rate training to optimise the character error rate of the output---the feature weights are tuned to optimize bleu using the minimum error rate training algorithm | 1 |
removing the power of higher order language model and longer max phrase length , which are inherent in pseudowords , shows that pseudowords still improve translational performance significantly over unary words---of removing the power of higher order language model and longer max phrase length , which are inherent in pseudowords , show that pseudowords still improve translational performance significantly over unary words | 1 |
we report large increases in accuracy over single-tagging at only a small cost in increased ambiguity---we have increased pos tagging accuracy significantly with only a tiny ambiguity penalty | 1 |
we use word2vec 1 toolkit to pre-train the character embeddings on the chinese wikipedia corpus---to get a dictionary of word embeddings , we use the word2vec tool 2 and train it on the chinese gigaword corpus | 1 |
we used cdec as our hierarchical phrase-based decoder , and tuned the parameters of the system to optimize bleu on the nist mt06 corpus---grammars were extracted from the resulting parallel text and used in our hierarchical phrase-based system using cdec as the decoder | 1 |
the dashed line indicates an implicit relation in the phrase table---dotted line indicates an implicit relation in the phrase table | 1 |
twitter 1 is a microblogging service , which according to latest statistics , has 284 million active users , 77 % outside the us that generate 500 million tweets a day in 35 different languages---twitter is a microblogging social network launched in 2006 with 310 million active users per month and where 340 million tweets are daily generated 1 | 1 |
in this paper , we solve this issue by enriching the feature representations for a graph-based model using a dependency language model ( dlm ) ( cite-p-27-3-21 )---in this paper , we present an approach to enriching high-order feature representations for graph-based dependency parsing models | 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 have used the srilm with kneser-ney smoothing for training a language model for the first stage of decoding | 1 |
with additional lexical knowledge from wordnet , performance is further improved to surpass the state-of-the-art results---with additional lexical knowledge , the model also outperformed state of the art results | 1 |
as a result , an argument model is needed to identify linguistically plausible spanning trees---and an argument model finds trees that are linguistically more plausible | 1 |
to exploit these kind of labeling constraints , we resort to conditional random fields---both our constrained and unconstrained systems use conditional random fields | 1 |
it has been shown that images from google yield higher-quality representations than comparable sources such as flickr---it has been shown that images from google yield higher quality representations than comparable resources such as flickr and are competitive with hand-crafted datasets | 1 |
when evaluated on the newly released , large semantic parsing dataset , wikisql , our approach leads to faster convergence and enjoys 1.1 % –5.4 % absolute accuracy gains over the non-meta-learning counterparts , achieving a new state-of-the-art result---two such successful statistical nlg systems are nitrogen and oxygen | 0 |
we use distributed word vectors trained on the wikipedia corpus using the word2vec algorithm---on all datasets and models , we use 300-dimensional word vectors pre-trained on google news | 1 |
coreference resolution is the process of linking multiple mentions that refer 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 |
furthermore , we train a 5-gram language model using the sri language toolkit---we train a trigram language model with the srilm toolkit | 1 |
hirst shows that even simple cases lead to a multiplicity of nearly identical concepts , thereby defeating the purpose of a language-independent ontology---hirst showed that such a model entails an awkward taxonomic proliferation of language-specific concepts at the fringes , thereby defeating the purpose of a language-independent ontology | 1 |
jeon et al presented question retrieval methods that are based on using the similarity between answers in the archive to estimate probabilities for a translation-based retrieval model---we conduct experiments for uncertainty post identification and study the effectiveness of different categories of features based on the generated corpus | 0 |
experimental results suggest that they rival standard reference-based metrics in terms of correlations with human judgments on new test instances---experimental results suggest that a regression-trained metric that compares against pseudo references can have higher correlations with human judgments | 1 |
in an hscrf , word-level labels are utilized to derive the segment scores---word-level labels are utilized to derive the segment scores | 1 |
luong et al train a recursive neural network for morphological composition , and show its effectiveness on word similarity task---luong et al utilized the morpheme segments produced by morfessor and constructed morpheme trees for words to learn morphologically-aware word embeddings by the recursive neural network | 1 |
abstract meaning representation is a semantic formalism which represents sentence meaning in a form of a rooted directed acyclic graph---abstract meaning representation is a semantic representation where the meaning of a sentence is encoded as a rooted , directed and acyclic graph | 1 |
recently , significant progress has been made in learning semantic parsers for large knowledge bases such as freebase---finally , some work has looked at applying semantic parsing to answer queries against large knowledge bases , such as yago and freebase | 1 |
relation extraction is a core task in information extraction and natural language understanding---relation extraction ( re ) is the task of recognizing relationships between entities mentioned in text | 1 |
hierarchical phrase-based translation models that utilize synchronous context free grammars have been widely adopted in statistical machine translation---probabilistic synchronous grammars are widely used in statistical machine translation and semantic parsing | 1 |
we use the adam optimizer and mini-batch gradient to solve this optimization problem---a tri-gram local language model is built over the target side of the training corpus with the irstlm toolkit | 0 |
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