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This paper talks about KenLM: Faster and Smaller Language Model Queries. | 0 | These packages are further described in Section 3. |
They plan on extending instance-weighting to other standard SMT components and capture the degree of generality of phrase pairs. | 0 | In this paper we study the problem of using a parallel corpus from a background domain (OUT) to improve performance on a target domain (IN) for which a smaller amount of parallel training material—though adequate for reasonable performance—is also available. |
They have made use of local and global features to deal with the instances of same token in a document. | 0 | Hence, for each token, one of the four features zone-TXT, zone- HL, zone-DATELINE, or zone-DD is set to 1, and the other 3 are set to 0. |
The fact that projective dependency parsers can never exactly reproduce the analyses found in non-projective tree banks is often neglected because of the relative scarcity of problematic constructions. | 0 | It is likely that the more complex cases, where path information could make a difference, are beyond the reach of the parser in most cases. |
This paper presents methods to query N-gram language models, minimizing time and space costs. | 0 | Backoff-smoothed models estimate this probability based on the observed entry with longest matching history wnf , returning where the probability p(wn|wn−1 f ) and backoff penalties b(wn−1 i ) are given by an already-estimated model. |
Human judges also pointed out difficulties with the evaluation of long sentences. | 0 | HR0011-06-C-0022. |
The second algorithm builds on a boosting algorithm called AdaBoost. | 0 | We again adopt an approach where we alternate between two classifiers: one classifier is modified while the other remains fixed. |
Other kinds of productive word classes, such as company names, abbreviations,and place names can easily be handled given appropriate models. | 0 | 3. |
In this paper, the authors are of the opinion that the sequence models-based approaches usually treat token-level tag assignment as the primary latent variable. | 0 | Once HMM parameters (θ, Ï) are drawn, a token-level tag and word sequence, (t, w), is generated in the standard HMM fashion: a tag sequence t is generated from Ï. |
In this paper, Ben and Riloff present a coreference resolver called BABAR that focuses on the use of contextual-role knowledge for coreference resolution. | 0 | Table 3 shows BABARâs performance when the four contextual role knowledge sources are added. |
It is probably the first analysis of Arabic parsing of this kind. | 0 | With a human evaluation we also showed that ATB inter-annotator agreement remains low relative to the WSJ corpus. |
One can trivially create situations in which strictly binary-branching trees are combined to create a tree with only the root node and the terminal nodes, a completely flat structure. | 0 | The estimation of the probabilities in the model is carried out as shown in Equation 4. |
From a DP-based solution to the traveling salesman problem, they present a novel technique to restrict the possible word reordering between source and target language in order to achieve an eÃcient search algorithm. | 0 | 3.2 Reordering with IBM Style. |
In this paper the authors present a stochastic finite-state model for segmenting Chinese text into words. | 0 | JA DE G O L D G R AS S SI C K NE SS DE AT H R A T 14. |
Finally, several coreference systems have successfully incorporated anaphoricity determination modules. | 0 | If these sets do not overlap, then the words cannot be coreferent. |
The authors use linguistic and annotation insights to develop a manually annotated grammar and evaluate it and finally provide a realistic evaluation in which segmentation is performed in a pipeline jointly with parsing. | 0 | We extend the Stanford parser to accept pre-generated lattices, where each word is represented as a finite state automaton. |
They proposed an unsupervised method to discover paraphrases from a large untagged corpus. | 0 | There have been other kinds of efforts to discover paraphrase automatically from corpora. |
The model incorporates various recent techniques for incorporating and manipulating linguistic knowledge using finite-state transducers. | 0 | We can model this probability straightforwardly enough with a probabilistic version of the grammar just given, which would assign probabilities to the individual rules. |
The PROBING data structure uses linear probing hash tables and is designed for speed. | 0 | While we have minimized forward-looking state in Section 4.1, machine translation systems could also benefit by minimizing backward-looking state. |
The first method builds on results from (Yarowsky 95) and (Blum and Mitchell 98). | 0 | (2) was extended to have an additional, innermost loop over the (3) possible labels. |
The authors use linguistic and annotation insights to develop a manually annotated grammar and evaluate it and finally provide a realistic evaluation in which segmentation is performed in a pipeline jointly with parsing. | 0 | At the phrasal level, we remove all function tags and traces. |
Throughout this paper we compare with several packages: SRILM 1.5.12 (Stolcke, 2002) is a popular toolkit based on tries used in several decoders. | 0 | Compared to decoding, this task is cache-unfriendly in that repeated queries happen only as they naturally occur in text. |
The first method builds on results from (Yarowsky 95) and (Blum and Mitchell 98). | 0 | The second algorithm builds on a boosting algorithm called AdaBoost (Freund and Schapire 97; Schapire and Singer 98). |
NER is useful in many NLP applications such as information extraction, question answering, etc .Chieu and Ng have shown that the maximum entropy framework is able to use global information directly from various sources. | 0 | needs to be in initCaps to be considered for this feature. |
Two general approaches are presented and two combination techniques are described for each approach. | 0 | It is possible one could produce better models by introducing features describing constituents and their contexts because one parser could be much better than the majority of the others in particular situations. |
This paper talks about Pseudo-Projective Dependency Parsing. | 0 | The most informative scheme, Head+Path, gives the highest scores, although with respect to Head the difference is not statistically significant, while the least informative scheme, Path – with almost the same performance on treebank transformation – is significantly lower (p < 0.01). |
A large number of rules are needed for coverage of the domain, suggesting that a fairly large number of labeled examples should be required to train a classifier. | 0 | Fig. |
In this paper the authors present a stochastic finite-state model for segmenting Chinese text into words. | 0 | The transition from f, to a final state transduces c to the grammatical tag PL with cost cost(unseen(f,)): cost(i¥JJ1l.ir,) == cost(i¥JJ1l.) |
While many systems had similar performance, the results offered interesting insights, especially, about the relative performance of statistical and rule-based systems. | 0 | Presenting the output of several system allows the human judge to make more informed judgements, contrasting the quality of the different systems. |
The resulting model is compact, efficiently learnable and linguistically expressive. | 0 | Simply assigning to each word its most frequent associated tag in a corpus achieves 94.6% accuracy on the WSJ portion of the Penn Treebank. |
Bean and Riloff also used bootstrapping to extend their semantic compatibility model, proposed using caseframe network for anaphora resolution, information extraction patterns to identify contextual clues for determining compatibility between NPs. | 0 | BABAR uses two methods to identify anaphors that can be easily and reliably resolved with their antecedent: lexical seeding and syntactic seeding. |
There is no global pruning. | 0 | A straightforward way to find the shortest tour is by trying all possible permutations of the n cities. |
Other kinds of productive word classes, such as company names, abbreviations,and place names can easily be handled given appropriate models. | 0 | na me =>2 ha nzi fa mi ly 2 ha nzi gi ve n 5. |
They employed a PCFG-based generative framework to make both syntactic and morphological disambiguation decisions which were not only theoretically clean and linguistically justified but also probabilistically appropriate and empirically sound. | 0 | Co-occurrences among the particles themselves are subject to further syntactic and lexical constraints relative to the stem. |
In this work, they take a more direct approach and treat a word type and its allowed POS tags as a primary element of the model. | 0 | However, our full model takes advantage of word features not present in Grac¸a et al. |
The overall parsing accuracy obtained with the pseudo-projective approach is still lower than for the best projective parsers. | 0 | The most informative scheme, Head+Path, gives the highest scores, although with respect to Head the difference is not statistically significant, while the least informative scheme, Path – with almost the same performance on treebank transformation – is significantly lower (p < 0.01). |
The use of global features has shown excellent result in the performance on MUC-6 and MUC-7 test data. | 0 | The reason why we did not train with both MUC6 and MUC7 training data at the same time is because the task specifications for the two tasks are not identical. |
Das and Petrov, in this paper, approached inducing unsupervised part-of-speech taggers for languages that had no labeled training data, but had translated text in a resource-rich language. | 0 | It would have therefore also been possible to use the integer programming (IP) based approach of Ravi and Knight (2009) instead of the feature-HMM for POS induction on the foreign side. |
Most IE researchers have been creating paraphrase knowledge by hand and specific tasks. | 0 | The most frequent NE category pairs are âPerson - Person (209,236), followed by âCountry - Coun- tryâ (95,123) and âPerson - Countryâ (75,509). |
The authors cluster NE instance pairs based on the words in the context using bag-of-words methods. | 0 | We are focusing on phrases which have two Named Entities (NEs), as those types of phrases are very important for IE applications. |
This assumption, however, is not inherent to type-based tagging models. | 0 | 4 53.7 43. |
The texts were annotated with the RSTtool. | 0 | For one thing, it is not clear who is to receive settlements or what should happen in case not enough teachers accept the offer of early retirement. |
The manual evaluation of scoring translation on a graded scale from 1â5 seems to be very hard to perform. | 0 | So, who won the competition? |
Evaluation was done automatically using the BLEU score and manually on fluency and adequacy. | 0 | Figure 1 provides some statistics about this corpus. |
The departure from the traditional token-based tagging approach allow them to explicitly capture type-level distributional properties of valid POS tag assignments as part of the model. | 0 | 0 68.4 48. |
NER is useful in many NLP applications such as information extraction, question answering, etc .Chieu and Ng have shown that the maximum entropy framework is able to use global information directly from various sources. | 0 | To eliminate such sequences, we define a transition probability between word classes to be equal to 1 if the sequence is admissible, and 0 otherwise. |
All the texts were annotated by two people. | 0 | It is difficult to motivate these days why one ministry should be exempt from cutbacks â at the expense of the others. |
The PROBING data structure uses linear probing hash tables and is designed for speed. | 0 | For even larger models, we recommend RandLM; the memory consumption of the cache is not expected to grow with model size, and it has been reported to scale well. |
Combining multiple highly-accurate independent parsers yields promising results. | 0 | A receives a votes, and B receives b votes. |
They showed better grammars to improve performance on both morphological and syntactic tasks, providing support for the advantage of a joint framework over pipelined or factorized ones. | 0 | The correct ambiguity resolution of the syntactic level therefore helps to resolve the morphological one, and vice versa. |
Throughout this paper we compare with several packages: SRILM 1.5.12 (Stolcke, 2002) is a popular toolkit based on tries used in several decoders. | 0 | It also uses less memory, with 8 bytes of overhead per entry (we store 16-byte entries with m = 1.5); linked list implementations hash set and unordered require at least 8 bytes per entry for pointers. |
The approach assumes that the word reordering is restricted to a few positions in the source sentence. | 0 | The cities of the traveling salesman problem correspond to source Table 1: DP algorithm for statistical machine translation. |
The evaluation compares the performance of the system with that of several human judges and inter-human agreement on a single correct way to segment a text. | 0 | gaolxing4 'happy' => F.i'JF.i'J Jl! |
Other kinds of productive word classes, such as company names, abbreviations,and place names can easily be handled given appropriate models. | 0 | This model is easily incorporated into the segmenter by building a WFST restrict ing the names to the four licit types, with costs on the arcs for any particular name summing to an estimate of the cost of that name. |
It is well-known that English constituency parsing models do not generalize to other languages and treebanks. | 0 | 49 99. |
There is no global pruning. | 0 | Skipped (K): The translation of up to one word may be postponed . Verb (V): The translation of up to two words may be anticipated. |
Here we show how non-projective dependency parsing can be achieved by combining a data driven projective parser with special graph transformation techniques. | 0 | The main result is that the combined system can recover non-projective dependencies with a precision sufficient to give a significant improvement in overall parsing accuracy, especially with respect to the exact match criterion, leading to the best reported performance for robust non-projective parsing of Czech. |
The TRIE model uses less memory than the smallest lossless alternative and is still faster than SRILM. | 0 | Memory usage is the same as with binary search and lower than with set. |
They proposed an unsupervised method to discover paraphrases from a large untagged corpus. | 0 | The NE tagger is a rule-based system with 140 NE categories [Sekine et al. 2004]. |
NER is useful in many NLP applications such as information extraction, question answering, etc .Chieu and Ng have shown that the maximum entropy framework is able to use global information directly from various sources. | 0 | This group contains a large number of features (one for each token string present in the training data). |
The main result is that the combined system can recover non-projective dependencies with a precision sufficient to give a significant improvement in overall parsing accuracy, especially with respect to the exact match criterion, leading to the best reported performance for robust non-projective parsing of Czech. | 0 | However, this argument is only plausible if the formal framework allows non-projective dependency structures, i.e. structures where a head and its dependents may correspond to a discontinuous constituent. |
The code is open source, has minimal dependencies, and offers both C++ and Java interfaces for integration. | 0 | Then we ran binary search to determine the least amount of memory with which it would run. |
The manual evaluation of scoring translation on a graded scale from 1–5 seemed to be very hard to perform. | 0 | Manual and Automatic Evaluation of Machine Translation between European Languages |
The authors cluster NE instance pairs based on the words in the context using bag-of-words methods. | 0 | Up to now, most IE researchers have been creating paraphrase knowledge (or IE patterns) by hand and for specific tasks. |
They showed better grammars to improve performance on both morphological and syntactic tasks, providing support for the advantage of a joint framework over pipelined or factorized ones. | 0 | “in the shadow”. |
A large number of rules are needed for coverage of the domain, suggesting that a fairly large number of labeled examples should be required to train a classifier. | 0 | We define the following function: If Zco is small, then it follows that the two classifiers must have a low error rate on the labeled examples, and that they also must give the same label on a large number of unlabeled instances. |
BABAR's performance in both domains of terrorism and natural disaster, and the contextual-role knowledge in pronouns have shown successful results. | 0 | Ex: The government said it ... |
The manual evaluation of scoring translation on a graded scale from 1â5 seems to be very hard to perform. | 0 | We therefore also normalized judgements on a per-sentence basis. |
The three parsers were trained and tuned by their creators on various sections of the WSJ portion of the Penn Treebank. | 0 | The natural language processing community is in the strong position of having many available approaches to solving some of its most fundamental problems. |
The contextual rules are restricted and may not be applicable to every example, but the spelling rules are generally applicable and should have good coverage. | 0 | For the purposes of EM, the "observed" data is {(xi, Ya• • • (xrn, Yrn), xfil, and the hidden data is {ym+i y}. |
Their empirical results demonstrate that the type-based tagger rivals state-of-the-art tag-level taggers which employ more sophisticated learning mechanisms to exploit similar constraints. | 0 | 1 61.7 37. |
They proposed an unsupervised method to discover paraphrases from a large untagged corpus. | 0 | Keyword detection error Even if a keyword consists of a single word, there are words which are not desirable as keywords for a domain. |
Replacing this with a ranked evaluation seems to be more suitable. | 0 | Presenting the output of several system allows the human judge to make more informed judgements, contrasting the quality of the different systems. |
The first method builds on results from (Yarowsky 95) and (Blum and Mitchell 98). | 0 | (4) gives In order to minimize Zt, at each iteration the final algorithm should choose the weak hypothesis (i.e., a feature xt) which has values for W+ and W_ that minimize Equ. |
Here we present two algorithms. | 0 | Finally, we would like to note that it is possible to devise similar algorithms based with other objective functions than the one given in Equ. |
They proposed an unsupervised method to discover paraphrases from a large untagged corpus. | 0 | Figure 3 Figure 1. |
They found replacing it with a ranked evaluation to be more suitable. | 0 | The bootstrap method has been critized by Riezler and Maxwell (2005) and Collins et al. (2005), as being too optimistic in deciding for statistical significant difference between systems. |
This paper talks about Exploiting Diversity in Natural Language Processing: Combining Parsers. | 0 | Consider for a set of constituents the isolated constituent precision parser metric, the portion of isolated constituents that are correctly hypothesized. |
the "Potsdam Commentary Corpus" or PCC consists of 170 commentaries from Ma¨rkische Allgemeine Zeitung, a German regional daily. | 0 | Figure 1: Translation of PCC sample commentary (STTS)2. |
The first method builds on results from (Yarowsky 95) and (Blum and Mitchell 98). | 0 | Taking only the highest frequency rules is much "safer", as they tend to be very accurate. |
Evaluation was done automatically using the BLEU score and manually on fluency and adequacy. | 0 | The test set included 2000 sentences from the Europarl corpus, but also 1064 sentences out-ofdomain test data. |
The model incorporates various recent techniques for incorporating and manipulating linguistic knowledge using finite-state transducers. | 0 | Note that the good classes JADE, GOLD and GRASS have lower costs than the bad classes SICKNESS, DEATH and RAT, as desired, so the trend observed for the results of this method is in the right direction. |
The resulting model is compact, efficiently learnable and linguistically expressive. | 0 | 1 55.8 38. |
It also incorporates the Good-Turing methodin estimating the likelihoods of previously unseen constructions, including morphological derivatives and personal names. | 0 | Note that Wang, Li, and Chang's. |
It is well-known that English constituency parsing models do not generalize to other languages and treebanks. | 0 | But Arabic contains a variety of linguistic phenomena unseen in English. |
Explanations for this phenomenon are relative informativeness of lexicalization, insensitivity to morphology and the effect of variable word order and these factors lead to syntactic disambiguation. | 0 | 27 80. |
A beam search concept is applied as in speech recognition. | 0 | The Levenshtein distance between the automatic translation and each of the reference translations is computed, and the minimum Levenshtein distance is taken. |
The contextual rules are restricted and may not be applicable to every example, but the spelling rules are generally applicable and should have good coverage. | 0 | Thus at each iteration the method induces at most n x k rules, where k is the number of possible labels (k = 3 in the experiments in this paper). step 3. |
Their empirical results demonstrate that the type-based tagger rivals state-of-the-art tag-level taggers which employ more sophisticated learning mechanisms to exploit similar constraints. | 0 | Our work is closely related to recent approaches that incorporate the sparsity constraint into the POS induction process. |
Finally, several coreference systems have successfully incorporated anaphoricity determination modules. | 0 | In recent years, coreference resolvers have been evaluated as part of MUC6 and MUC7 (MUC7 Proceedings, 1998). |
The model incorporates various recent techniques for incorporating and manipulating linguistic knowledge using finite-state transducers. | 0 | This Good Turing estimate of p(unseen(f,) If,) can then be used in the normal way to define the probability of finding a novel instance of a construction in ir, in a text: p(unseen(f,)) = p(unseen(f,) I f,) p(fn Here p(ir,) is just the probability of any construction in ft as estimated from the frequency of such constructions in the corpus. |
Koehn and Monz carried out an extensive manual and automatic evaluation of machine translation performance on European language pairs. | 0 | While we used the standard metrics of the community, the we way presented translations and prompted for assessment differed from other evaluation campaigns. |
All the texts were annotated by two people. | 0 | The kind of annotation work presented here would clearly benefit from the emergence of standard formats and tag sets, which could lead to sharable resources of larger size. |
Evaluation was done automatically using the BLEU score and manually on fluency and adequacy. | 0 | This is can not be the only explanation, since the discrepancy still holds, for instance, for out-of-domain French-English, where Systran receives among the best adequacy and fluency scores, but a worse BLEU score than all but one statistical system. |
The authors use linguistic and annotation insights to develop a manually annotated grammar and evaluate it and finally provide a realistic evaluation in which segmentation is performed in a pipeline jointly with parsing. | 0 | Therefore, we only score guess/gold pairs with identical character yields, a condition that allows us to measure parsing, tagging, and segmentation accuracy by ignoring whitespace. |
Other kinds of productive word classes, such as company names, abbreviations,and place names can easily be handled given appropriate models. | 0 | (In this figure eps is c) be implemented, though, such as a maximal-grouping strategy (as suggested by one reviewer of this paper); or a pairwise-grouping strategy, whereby long sequences of unattached hanzi are grouped into two-hanzi words (which may have some prosodic motivation). |
The authors show that PATB is similar to other tree-banks but that annotation consistency remains low. | 0 | All three models evaluated in this paper incorrectly analyze the constituent as iDafa; none of the models attach the attributive adjectives properly. |
They showed the efficacy of graph-based label propagation for projecting part-of-speech information across languages. | 0 | The first term in the objective function is the graph smoothness regularizer which encourages the distributions of similar vertices (large wij) to be similar. |
It also incorporates the Good-Turing methodin estimating the likelihoods of previously unseen constructions, including morphological derivatives and personal names. | 0 | May 1995). |
Here both parametric and non-parametric models are explored. | 0 | It is possible one could produce better models by introducing features describing constituents and their contexts because one parser could be much better than the majority of the others in particular situations. |
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