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This paper presents methods to query N-gram language models, minimizing time and space costs. | 0 | An important subproblem of language model storage is therefore sparse mapping: storing values for sparse keys using little memory then retrieving values given keys using little time. |
This corpus has several advantages: it is annotated at different levels. | 0 | Figure 2 shows a screenshot (which is of somewhat limited value, though, as color plays a major role in signalling the different statuses of the information). |
The resulting model is compact, efficiently learnable and linguistically expressive. | 0 | 36. |
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 | -1 means that an NP should be ruled out as a possible antecedent, and 0 means that the knowledge source remains neutral (i.e., it has no reason to believe that they cannot be coreferent). |
This paper presents methods to query N-gram language models, minimizing time and space costs. | 0 | Most similar is scrolling queries, wherein left-to-right queries that add one word at a time are optimized. |
Nevertheless, only a part of this corpus (10 texts), which the authors name "core corpus", is annotated with all this information. | 0 | Text generation, or at least the two phases of text planning and sentence planning, is a process driven partly by well-motivated choices (e.g., use this lexeme X rather than that more colloquial near-synonym Y ) and partly by con tation like that of PCC can be exploited to look for correlations in particular between sy... |
The authors show that PATB is similar to other tree-banks but that annotation consistency remains low. | 0 | Our results suggest that current parsing models would benefit from better annotation consistency and enriched annotation in certain syntactic configurations. |
The texts were annotated with the RSTtool. | 0 | There is a âcore corpusâ of ten commentaries, for which the range of information (except for syntax) has been completed; the remaining data has been annotated to different degrees, as explained below. |
This paper presents a maximum entropy-based named entity recognizer (NER). | 0 | Mikheev et al. |
Evaluation was done automatically using the BLEU score and manually on fluency and adequacy. | 0 | Judges where excluded from assessing the quality of MT systems that were submitted by their institution. |
Through parser combination we have reduced the precision error rate by 30% and the recall error rate by 6% compared to the best previously published result. | 0 | First we present the non-parametric version of parser switching, similarity switching: The intuition for this technique is that we can measure a similarity between parses by counting the constituents they have in common. |
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 | As such, global information from the whole context of a document is important to more accurately recognize named entities. |
BABAR's performance in both domains of terrorism and natural disaster, and the contextual-role knowledge in pronouns have shown successful results. | 0 | Finally, a DempsterShafer probabilistic model evaluates the evidence provided by the knowledge sources for all candidate antecedents and makes the final resolution decision. |
In this paper the authors present a stochastic finite-state model for segmenting Chinese text into words. | 0 | The most popular approach to dealing with seg mentation ambiguities is the maximum matching method, possibly augmented with further heuristics. |
Evaluation was done automatically using the BLEU score and manually on fluency and adequacy. | 0 | English was again paired with German, French, and Spanish. |
Across eight European languages, their approach results in an average absolute improvement of 10.4% over a state-of-the-art baseline, and 16.7% over vanilla hidden Markov models induced with the Expectation Maximization algorithm. | 0 | To this end, we construct a bilingual graph over word types to establish a connection between the two languages (§3), and then use graph label propagation to project syntactic information from English to the foreign language (§4). |
they showed that the average agreement among the human judges is .76, and the average agreement between ST(system) and the humans is .75, or about 99% of the interhuman agreement. | 0 | 25 16. |
Here both parametric and non-parametric models are explored. | 0 | All four of the techniques studied result in parsing systems that perform better than any previously reported. |
It also incorporates the Good-Turing methodin estimating the likelihoods of previously unseen constructions, including morphological derivatives and personal names. | 0 | The percentage scores on the axis labels represent the amount of variation in the data explained by the dimension in question. |
The problem of coreference resolution has received considerable attention, including theoretical discourse models and supervised machine learning systems. | 0 | 3.2 The DempsterShafer Decision Model. |
It is probably the first analysis of Arabic parsing of this kind. | 0 | 31 75. |
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 | On each language we investigate the contribution of each component of our model. |
Here both parametric and non-parametric models are explored. | 0 | In general, the lemma of the previous section does not ensure that all the productions in the combined parse are found in the grammars of the member parsers. |
This assumption, however, is not inherent to type-based tagging models. | 0 | to explore how well we can induce POS tags using only the one-tag-per-word constraint. |
they evaluate various specific aspects of the segmentation, as well as the overall segmentation performance. | 0 | The performance was 80.99% recall and 61.83% precision. |
The three parsers were trained and tuned by their creators on various sections of the WSJ portion of the Penn Treebank. | 0 | The machine learning community has been in a similar situation and has studied the combination of multiple classifiers (Wolpert, 1992; Heath et al., 1996). |
This paper talks about Unsupervised Models for Named Entity Classification. | 0 | The approach gains leverage from natural redundancy in the data: for many named-entity instances both the spelling of the name and the context in which it appears are sufficient to determine its type. |
They proposed a single joint model for performing both morphological segmentation and syntactic disambiguation which bypasses the associated circularity. | 0 | Tsarfaty and Sima’an (2007) have reported state-of-the-art results on Hebrew unlexicalized parsing (74.41%) albeit assuming oracle morphological segmentation. |
A beam search concept is applied as in speech recognition. | 0 | No: Predecessor coverage set Successor coverage set 1 (f1; ;mg n flg ; l0) ! |
It is annotated with several data: morphology, syntax, rhetorical structure, connectors, correference and informative structure. | 0 | Thus we opted not to take the step of creating more precise written annotation guidelines (as (Carlson, Marcu 2001) did for English), which would then allow for measuring inter-annotator agreement. |
They have made use of local and global features to deal with the instances of same token in a document. | 0 | As each global feature group is added to the list of features, we see improvements to both MUC6 and MUC6 MUC7 Baseline 90.75% 85.22% + ICOC 91.50% 86.24% + CSPP 92.89% 86.96% + ACRO 93.04% 86.99% + SOIC 93.25% 87.22% + UNIQ 93.27% 87.24% Table 3: F-measure after successive addition of each global feature group Table 5:... |
The resulting model is compact, efficiently learnable and linguistically expressive. | 0 | Any opinions, findings, conclusions, or recommendations expressed in this paper are those of the authors, and do not necessarily reflect the views of the funding organizations. |
For the perplexity and translation tasks, we used SRILM to build a 5-gram English language model on 834 million tokens from Europarl v6 (Koehn, 2005) and the 2011 Workshop on Machine Translation News Crawl corpus with duplicate lines removed. | 0 | The problem is to store these two values for a large and sparse set of n-grams in a way that makes queries efficient. |
The TRIE model uses less memory than the smallest lossless alternative and is still faster than SRILM. | 0 | The developers suggested some changes, such as building the model from scratch with IRSTLM, but these did not resolve the problem. |
The texts were annotated with the RSTtool. | 0 | Future work along these lines will incorporate other layers of annotation, in particular the syntax information. |
They showed that it was useful to abstract away from the details of the formalism, and examine the nature of their derivation process as reflected by properties their trees, find that several of the formalisms considered can be seen as being closely related since they have derivation tree sets with the same structure a... | 0 | The following rule corresponds to the above derivation, where 71, , 7k are derived from the auxiliary trees , , fik, respectively. for all addresses n in some elementary tree at which 7' can be adjoined. |
They showed that it was useful to abstract away from the details of the formalism, and examine the nature of their derivation process as reflected by properties their trees, find that several of the formalisms considered can be seen as being closely related since they have derivation tree sets with the same structure a... | 0 | Thus, for example, one successor process will be have M to be in the existential state qa with the indices encoding xi , , xn, in the first 2n i tapes. |
It is probably the first analysis of Arabic parsing of this kind. | 0 | Table 9 shows that MADA produces a high quality segmentation, and that the effect of cascading segmentation errors on parsing is only 1.92% F1. |
In this paper the author evaluates machine translation performance for six European language pairs that participated in a shared task: translating French, German, Spanish texts to English and back. | 0 | Following this method, we repeatedly — say, 1000 times — sample sets of sentences from the output of each system, measure their BLEU score, and use these 1000 BLEU scores as basis for estimating a confidence interval. |
The TRIE model uses less memory than the smallest lossless alternative and is still faster than SRILM. | 0 | Unigram lookup is dense so we use an array of probability and backoff values. |
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 | These methods demonstrated the benefits of incorporating linguistic features using a log-linear parameterization, but requires elaborate machinery for training. |
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 | In the next section we present an alternative approach that builds two classifiers while attempting to satisfy the above constraints as much as possible. |
This paper conducted research in the area of automatic paraphrase discovery. | 0 | This paper does not necessarily reflect the position of the U.S. Government. |
Using a treebank grammar, the data-driven lexicon, and a linguistically motivated unknown-tokens handling technique their model outperformed previous pipelined, integrated or factorized systems for Hebrew morphological and syntactic processing, yielding an error reduction of 12% over the best published results so far. | 0 | In our forth model GTnph we add the definiteness status of constituents following Tsarfaty and Sima’an (2007). |
The three parsers were trained and tuned by their creators on various sections of the WSJ portion of the Penn Treebank. | 0 | Hence, s < k. But by addition of the votes on the two parses, s > 2N-11> k, a contradiction. |
This architecture provides a uniform framework in which it is easy to incorporate not only listed dictionary entries but also morphological derivatives, and models for personal names and foreign names in transliteration. | 0 | The first issue relates to the completeness of the base lexicon. |
The TRIE model uses less memory than the smallest lossless alternative and is still faster than SRILM. | 0 | Typical data structures are generalized Bloom filters that guarantee a customizable probability of returning the correct answer. |
They believe that global context is useful in most languages, as it is a natural tendency for authors to use abbreviations on entities already mentioned previously. | 0 | The system described in this paper is similar to the MENE system of (Borthwick, 1999). |
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 | Memory usage is likely much lower than ours. fThe original paper (Germann et al., 2009) provided only 2s of query timing and compared with SRI when it exceeded available RAM. |
The PROBING data structure uses linear probing hash tables and is designed for speed. | 0 | Finally, other packages implement language model estimation while we are currently dependent on them to generate an ARPA file. |
The approach assumes that the word reordering is restricted to a few positions in the source sentence. | 0 | Depending on the threshold t0, the search algorithm may miss the globally optimal path which typically results in additional translation errors. |
An extended lexicon model is defined, and its likelihood is compared to a baseline lexicon model, which takes only single-word dependencies into account. | 0 | On average, 6 reference translations per automatic translation are available. |
BABAR's performance in both domains of terrorism and natural disaster, and the contextual-role knowledge in pronouns have shown successful results. | 0 | Contextual role knowledge provides evidence as to whether a candidate is a plausible antecedent for an anaphor. |
In this paper the authors present a stochastic finite-state model for segmenting Chinese text into words. | 0 | Thus in a two-hanzi word like lflli?J zhong1guo2 (middle country) 'China' there are two syllables, and at the same time two morphemes. |
Their results suggested that it was possible to learn accurate POS taggers for languages which did not have any annotated data, but have translations into a resource-rich language. | 0 | For monolingual treebank data we relied on the CoNLL-X and CoNLL-2007 shared tasks on dependency parsing (Buchholz and Marsi, 2006; Nivre et al., 2007). |
These clusters are computed using an SVD variant without relying on transitional structure. | 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. |
Here we present two algorithms. | 0 | The approach gains leverage from natural redundancy in the data: for many named-entity instances both the spelling of the name and the context in which it appears are sufficient to determine its type. |
They proposed a single joint model for performing both morphological segmentation and syntactic disambiguation which bypasses the associated circularity. | 0 | We use double-circles to indicate the space-delimited token boundaries. |
This paper offers a broad insight into of Arabic constituency parsing by analyzing the interplay of linguistic phenomena, annotation choices, and model design. | 0 | 99 94. |
The authors show that PATB is similar to other tree-banks but that annotation consistency remains low. | 0 | We extend the Stanford parser to accept pre-generated lattices, where each word is represented as a finite state automaton. |
they showed that the average agreement among the human judges is .76, and the average agreement between ST(system) and the humans is .75, or about 99% of the interhuman agreement. | 0 | The cost estimate, cost(i¥JJ1l.fn is computed in the obvious way by summing the negative log probabilities of i¥JJ1l. |
Vijay-Shankar et all considered the structural descriptions produced by various grammatical formalisms in terms of the complexity of the paths and the relationship between paths in the sets of structural descriptions that each system can generate. | 0 | As a result, CFG's can not provide the structural descriptions in which there are nested dependencies between symbols labelling a path. |
Most IE researchers have been creating paraphrase knowledge by hand and specific tasks. | 0 | Evaluation results for links |
The manual evaluation of scoring translation on a graded scale from 1â5 seems to be very hard to perform. | 0 | In words, the judgements are normalized, so that the average normalized judgement per judge is 3. |
Their work is closely related to recent approaches that incorporate the sparsity constraint into the POS induction process. | 0 | 5 60.6 Table 3: Multilingual Results: We report token-level one-to-one and many-to-one accuracy on a variety of languages under several experimental settings (Section 5). |
It outperformed strong unsupervised baselines as well as approaches that relied on direct projections, and bridged the gap between purely supervised and unsupervised POS tagging models. | 0 | For English POS tagging, BergKirkpatrick et al. (2010) found that this direct gradient method performed better (>7% absolute accuracy) than using a feature-enhanced modification of the Expectation-Maximization (EM) algorithm (Dempster et al., 1977).8 Moreover, this route of optimization outperformed a vanilla HMM train... |
These clusters are computed using an SVD variant without relying on transitional structure. | 0 | Previous work has attempted to incorporate such constraints into token-level models via heavy-handed modifications to inference procedure and objective function (e.g., posterior regularization and ILP decoding) (Grac¸a et al., 2009; Ravi and Knight, 2009). |
The overall parsing accuracy obtained with the pseudo-projective approach is still lower than for the best projective parsers. | 0 | Still, from a theoretical point of view, projective parsing of non-projective structures has the drawback that it rules out perfect accuracy even as an asymptotic goal. |
A beam search concept is applied as in speech recognition. | 0 | Table 5: Effect of the beam threshold on the number of search errors (147 sentences). |
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 | Figure 2: An ATB sample from the human evaluation. |
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 | The algorithm builds two classifiers iteratively: each iteration involves minimization of a continuously differential function which bounds the number of examples on which the two classifiers disagree. |
They proposed an unsupervised method to discover paraphrases from a large untagged corpus. | 0 | In our experiment, we set the threshold of the TF/ITF score empirically using a small development corpus; a finer adjustment of the threshold could reduce the number of such keywords. |
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 | The algorithm can be viewed as heuristically optimizing an objective function suggested by (Blum and Mitchell 98); empirically it is shown to be quite successful in optimizing this criterion. |
There are clustering approaches that assign a single POS tag to each word type. | 0 | See Section 5. |
They have made use of local and global features to deal with the instances of same token in a document. | 0 | MENE without Proteus, however, did not do very well and only achieved an F measure of 84.22% (Borthwick, 1999). |
They incorporated instance-weighting into a mixture-model framework, and found that it yielded consistent improvements over a wide range of baselines. | 0 | Second, rather than relying on a division of the corpus into manually-assigned portions, we use features intended to capture the usefulness of each phrase pair. |
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 | Pseudo-labels are formed by taking seed labels on the labeled examples, and the output of the fixed classifier on the unlabeled examples. |
This paper presents a maximum entropy-based named entity recognizer (NER). | 0 | Case and Zone of and : Similarly, if (or ) is initCaps, a feature (initCaps, zone) (or (initCaps, zone) ) is set to 1, etc. Token Information: This group consists of 10 features based on the string , as listed in Table 1. |
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 | For a given "word" in the automatic segmentation, if at least k of the hu man judges agree that this is a word, then that word is considered to be correct. |
The AdaBoost algorithm was developed for supervised learning. | 0 | Formally, let el (62) be the number of classification errors of the first (second) learner on the training data, and let Eco be the number of unlabeled examples on which the two classifiers disagree. |
Replacing this with a ranked evaluation seems to be more suitable. | 0 | However, ince we extracted the test corpus automatically from web sources, the reference translation was not always accurate — due to sentence alignment errors, or because translators did not adhere to a strict sentence-by-sentence translation (say, using pronouns when referring to entities mentioned in the previous se... |
In this paper, the authors proposed an approach for instance-weighting phrase pairs in an out-of-domain corpus in order to improve in-domain performance. | 0 | However, it is robust, efficient, and easy to implement.4 To perform the maximization in (7), we used the popular L-BFGS algorithm (Liu and Nocedal, 1989), which requires gradient information. |
There are clustering approaches that assign a single POS tag to each word type. | 0 | (2009). |
The second algorithm builds on a boosting algorithm called AdaBoost. | 0 | (6), with W+ > W_. |
They proposed a single joint model for performing both morphological segmentation and syntactic disambiguation which bypasses the associated circularity. | 0 | Given a PCFG grammar G and a lattice L with nodes n1 ... nk, we construct the weighted grammar GL as follows: for every arc (lexeme) l E L from node ni to node nj, we add to GL the rule [l --+ tni, tni+1, ... , tnj_1] with a probability of 1 (this indicates the lexeme l spans from node ni to node nj). |
Across eight European languages, their approach results in an average absolute improvement of 10.4% over a state-of-the-art baseline, and 16.7% over vanilla hidden Markov models induced with the Expectation Maximization algorithm. | 0 | When extracting the vector t, used to compute the constraint feature from the graph, we tried three threshold values for r (see Eq. |
In this paper, the authors proposed an approach for instance-weighting phrase pairs in an out-of-domain corpus in order to improve in-domain performance. | 0 | It is difficult when IN and OUT are dissimilar, as they are in the cases we study. |
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 | 2 We now introduce a new algorithm for learning from unlabeled examples, which we will call DLCoTrain (DL stands for decision list, the term Cotrain is taken from (Blum and Mitchell 98)). |
They extended previous work on discriminative weighting by using a finer granularity, focusing on the properties of instances rather than corpus components, and used simpler training procedure. | 0 | The final block in table 2 shows models trained on feature subsets and on the SVM feature described in 3.4. |
An extended lexicon model is defined, and its likelihood is compared to a baseline lexicon model, which takes only single-word dependencies into account. | 0 | The translation direction is from German to English. |
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 | Nicola Bertoldi and Marcello Federico assisted with IRSTLM. |
This assumption, however, is not inherent to type-based tagging models. | 0 | A more rigid mechanism for modeling sparsity is proposed by Ravi and Knight (2009), who minimize the size of tagging grammar as measured by the number of transition types. |
This paper presents a maximum entropy-based named entity recognizer (NER). | 0 | For corporate suffixes, a list of tokens cslist that occur frequently as the last token of an organization name is collected from the training data. |
They incorporated instance-weighting into a mixture-model framework, and found that it yielded consistent improvements over a wide range of baselines. | 0 | Sentence pairs are the natural instances for SMT, but sentences often contain a mix of domain-specific and general language. |
In this paper the authors present a stochastic finite-state model for segmenting Chinese text into words. | 0 | Of course, since the number of attested (phonemic) Mandarin syllables (roughly 1400, including tonal distinctions) is far smaller than the number of morphemes, it follows that a given syllable could in principle be written with any of several different hanzi, depending upon which morpheme is intended: the syllable zhon... |
The experimental tests are carried out on the Verbmobil task which is a limited-domain spoken-language task. | 0 | To be short, we omit the target words e; e0 in the formulation of the search hypotheses. |
Nevertheless, only a part of this corpus (10 texts), which the authors name "core corpus", is annotated with all this information. | 0 | This offers the well-known advantages for inter- changability, but it raises the question of how to query the corpus across levels of annotation. |
The PROBING data structure uses linear probing hash tables and is designed for speed. | 0 | Keys to the table are hashed, using for example Austin Appleby’s MurmurHash2, to integers evenly distributed over a large range. |
BABAR's performance in both domains of terrorism and natural disaster, and the contextual-role knowledge in pronouns have shown successful results. | 0 | BABAR uses unsupervised learning to acquire this knowledge from plain text without the need for annotated training data. |
It also incorporates the Good-Turing methodin estimating the likelihoods of previously unseen constructions, including morphological derivatives and personal names. | 0 | This is a rather important source of errors in name identifi cation, and it is not really possible to objectively evaluate a name recognition system without considering the main lexicon with which it is used. |
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