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The AdaBoost algorithm was developed for supervised learning. | 0 | Note, however, that there might be situations in which Zco in fact increases. |
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 | Ex: Mr. Cristiani is the president ... |
They have made use of local and global features to deal with the instances of same token in a document. | 0 | (1998) have also used a maximum entropy classifier that uses already tagged entities to help tag other entities. |
BABAR's performance in both domains of terrorism and natural disaster, and the contextual-role knowledge in pronouns have shown successful results. | 0 | Given an anaphor, BABAR identifies the caseframe that would extract it from its sentence. |
The authors cluster NE instance pairs based on the words in the context using bag-of-words methods. | 0 | Here a set is represented by the keyword and the number in parentheses indicates the number of shared NE pair instances. |
The authors show that PATB is similar to other tree-banks but that annotation consistency remains low. | 0 | As we have said, parse quality decreases with sentence length. |
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 | However, this optimistic search would not visit the entries necessary to store backoff information in the outgoing state. |
The use of global features has shown excellent result in the performance on MUC-6 and MUC-7 test data. | 0 | In fact, training on the official training data is not suitable as the articles in this data set are entirely about aviation disasters, and the test data is about air vehicle launching. |
The manual evaluation of scoring translation on a graded scale from 1â5 seems to be very hard to perform. | 0 | The judgement of 4 in the first case will go to a vastly better system output than in the second case. |
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. |
It is well-known that English constituency parsing models do not generalize to other languages and treebanks. | 0 | 6 Joint Segmentation and Parsing. |
All the texts were annotated by two people. | 0 | The tool we use is MMAX8, which has been specifically designed for marking co-reference. |
They used graph-based label propagation for cross-lingual knowledge transfer and used the projected labels as features in an unsupervised model. | 0 | Figure 2 shows an excerpt of a sentence from the Italian test set and the tags assigned by four different models, as well as the gold tags. |
In this paper the authors present a stochastic finite-state model for segmenting Chinese text into words. | 0 | 0 D/ nc 5.0 The minimal dictionary encoding this information is represented by the WFST in Figure 2(a). |
The authors cluster NE instance pairs based on the words in the context using bag-of-words methods. | 0 | In this domain the major scenarios involve the things they agreed on, rather than the mere fact that they agreed. |
This assumption, however, is not inherent to type-based tagging models. | 0 | During training, we treat as observed the language word types W as well as the token-level corpus w. We utilize Gibbs sampling to approximate our collapsed model posterior: P (T ,t|W , w, α, β) â P (T , t, W , w|α, β) 0.7 0.6 0.5 0.4 0.3 English Danish Dutch Germany Portuguese Spanish Swedish = P (T , t, W , w, Ï, θ, Ï, w|α, β)dÏdθdÏ Note that given tag assignments T , there is only one setting of token-level tags t which has mass in the above posterior. |
In order to handle the necessary word reordering as an optimization problem within the dynamic programming approach, they describe a solution to the traveling salesman problem (TSP) which is based on dynamic programming. | 0 | Additionally, for a given coverage set, at most 250 different hypotheses are kept during the search process, and the number of different words to be hypothesized by a source word is limited. |
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 | The possible analyses of a surface token pose constraints on the analyses of specific segments. |
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 | A detailed description of the search procedure used is given in this patent. |
The PROBING data structure uses linear probing hash tables and is designed for speed. | 0 | In this section, we extend state to optimize left-to-right queries. |
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 define a similarity function between the English and the foreign vertices, we rely on high-confidence word alignments. |
They have made use of local and global features to deal with the instances of same token in a document. | 0 | (1) CEO of McCann . . . |
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 corpus-based statistical parsing community has many fast and accurate automated parsing systems, including systems produced by Collins (1997), Charniak (1997) and Ratnaparkhi (1997). |
This paper presents a maximum entropy-based named entity recognizer (NER). | 0 | Hence we decided to restrict ourselves to only information from the same document. |
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 as those produced by Context-Free Grammars. | 0 | For example, Gazdar (1985) discusses the applicability of Indexed Grammars (IG's) to Natural Language in terms of the structural descriptions assigned; and Berwick (1984) discusses the strong generative capacity of Lexical-Functional Grammar (LFG) and Government and Bindings grammars (GB). |
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 as those produced by Context-Free Grammars. | 0 | He also argues that paired English complementizers may also require structural descriptions whose path sets have nested dependencies. |
The AdaBoost algorithm was developed for supervised learning. | 0 | AdaBoost was first introduced in (Freund and Schapire 97); (Schapire and Singer 98) gave a generalization of AdaBoost which we will use in this paper. |
The PROBING data structure uses linear probing hash tables and is designed for speed. | 0 | Though we are not able to calculate their memory usage on our model, results reported in their paper suggest lower memory consumption than TRIE on large-scale models, at the expense of CPU time. |
they evaluate various specific aspects of the segmentation, as well as the overall segmentation performance. | 0 | com t 700 Mountain Avenue, 2d451, Murray Hill, NJ 07974, USA. |
Human judges also pointed out difficulties with the evaluation of long sentences. | 0 | Hence, the different averages of manual scores for the different language pairs reflect the behaviour of the judges, not the quality of the systems on different language pairs. |
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 | These alignment models are similar to the concept of hidden Markov models (HMM) in speech recognition. |
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 | Maamouri et al. |
It is probably the first analysis of Arabic parsing of this kind. | 0 | We create equivalence classes for verb, noun, and adjective POS categories. |
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 | 25 16. |
Their work is closely related to recent approaches that incorporate the sparsity constraint into the POS induction process. | 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. |
It is probably the first analysis of Arabic parsing of this kind. | 0 | In Figure 4 we show an example of variation between the parsing models. |
This paper conducted research in the area of automatic paraphrase discovery. | 0 | Step 2. |
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 | The translation search is carried out with the category markers and the city names are resubstituted into the target sentence as a postprocessing step. |
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 | Since the transducers are built from human-readable descriptions using a lexical toolkit (Sproat 1995), the system is easily maintained and extended. |
This paper presents methods to query N-gram language models, minimizing time and space costs. | 0 | The developers suggested some changes, such as building the model from scratch with IRSTLM, but these did not resolve the problem. |
Human judges also pointed out difficulties with the evaluation of long sentences. | 0 | In Figure 4, we displayed the number of system comparisons, for which we concluded statistical significance. |
The PROBING data structure uses linear probing hash tables and is designed for speed. | 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. |
However, using the top-level semantic classes of WordNet proved to be problematic as the class distinctions are too coarse. | 0 | In our situation, the competing hypotheses are the possible antecedents for an anaphor. |
The model incorporates various recent techniques for incorporating and manipulating linguistic knowledge using finite-state transducers. | 0 | May 1995). |
Combining multiple highly-accurate independent parsers yields promising results. | 0 | The combining technique must act as a multi-position switch indicating which parser should be trusted for the particular sentence. |
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 | A Stochastic Finite-State Word-Segmentation Algorithm for Chinese |
The code is open source, has minimal dependencies, and offers both C++ and Java interfaces for integration. | 0 | In line with perplexity results from Table 1, the PROBING model is the fastest followed by TRIE, and subsequently other packages. |
This corpus has several advantages: it is annotated at different levels. | 0 | For effectively annotating connectives/scopes, we found that existing annotation tools were not well-suited, for two reasons: ⢠Some tools are dedicated to modes of annotation (e.g., tiers), which could only quite un-intuitively be used for connectives and scopes. |
The model incorporates various recent techniques for incorporating and manipulating linguistic knowledge using finite-state transducers. | 0 | Despite these limitations, a purely finite-state approach to Chinese word segmentation enjoys a number of strong advantages. |
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 | 4.1 Local Features. |
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 as those produced by Context-Free Grammars. | 0 | Analogous to the sharing of stacks in IC's, Lexical-Functional Grammar's (LFG's) use the unification of unbounded hierarchical structures. |
It is probably the first analysis of Arabic parsing of this kind. | 0 | In general, several gross corpus statistics favor the ATB, so other factors must contribute to parsing underperformance. |
Their work is closely related to recent approaches that incorporate the sparsity constraint into the POS induction process. | 0 | Another thread of relevant research has explored the use of features in unsupervised POS induction (Smith and Eisner, 2005; Berg-Kirkpatrick et al., 2010; Hasan and Ng, 2009). |
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 | 5 67.3 55. |
However, using the top-level semantic classes of WordNet proved to be problematic as the class distinctions are too coarse. | 0 | 6 Our knowledge sources return some sort of probability estimate, although in some cases this estimate is not especially well-principled (e.g., the Recency KS). |
Other kinds of productive word classes, such as company names, abbreviations,and place names can easily be handled given appropriate models. | 0 | A greedy algorithm (or maximum-matching algorithm), GR: proceed through the sentence, taking the longest match with a dictionary entry at each point. |
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 | Model components cascade, so the row corresponding to +FEATS also includes the PRIOR component (see Section 3). |
All the texts were annotated by two people. | 0 | Cur In order to ground such approaches in linguistic observation and description, a multi-level anno 10 For an exposition of the idea as applied to the task of text planning, see (Chiarcos, Stede 2004). |
They incorporated instance-weighting into a mixture-model framework, and found that it yielded consistent improvements over a wide range of baselines. | 0 | Previous approaches have tried to find examples that are similar to the target domain. |
Instance-weighting approach improved over a wide range of baselines, giving gains of over 2 BLEU points over the best non-adapted baseline. | 0 | We incorporate instance weighting into a mixture-model framework, and find that it yields consistent improvements over a wide range of baselines. |
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 | 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. |
This paper presents methods to query N-gram language models, minimizing time and space costs. | 0 | These packages are further described in Section 3. |
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 | level. |
The approach assumes that the word reordering is restricted to a few positions in the source sentence. | 0 | Otherwise for the predecessor search hypothesis, we would have chosen a position that would not have been among the first n uncovered positions. |
The bias of automatic methods in favour of statistical systems seemed to be less pronounced on out-of-domain test data. | 0 | Our initial experimentation with the evaluation tool showed that this is often too overwhelming. |
The bias of automatic methods in favour of statistical systems seems to be less pronounced on out-of-domain test data. | 0 | In words, the judgements are normalized, so that the average normalized judgement per judge is 3. |
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 | 63 81. |
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 | A named entity recognizer (NER) is useful in many NLP applications such as information extraction, question answering, etc. On its own, a NER can also provide users who are looking for person or organization names with quick information. |
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 | Semantic expectations are analogous to lexical expectations except that they represent semantic classes rather than nouns. |
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 as those produced by Context-Free Grammars. | 0 | Let n be some node labeled X in a tree -y (see Figure 3). |
They have made use of local and global features to deal with the instances of same token in a document. | 0 | (3)In sentence (1), McCann can be a person or an orga nization. |
It is probably the first analysis of Arabic parsing of this kind. | 0 | The pre terminal morphological analyses are mapped to the shortened âBiesâ tags provided with the tree- bank. |
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 | DempsterShafer handles this by re-normalizing all the belief values with respect to only the non-null sets (this is the purpose of the denominator in Equation 1). |
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 | Each name class is subdivided into 4 sub-classes, i.e., N begin, N continue, N end, and N unique. |
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 | The system of Berg-Kirkpatrick et al. |
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 | If enough parsers suggest that a particular constituent belongs in the parse, we include it. |
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 | One side of the decision making process is when we choose to believe a constituent should be in the parse, even though only one parser suggests it. |
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 | We adapt the string pumping lemma for the class of languages corresponding to the complexity of the path set. |
The first method builds on results from (Yarowsky 95) and (Blum and Mitchell 98). | 0 | On each step CoBoost searches for a feature and a weight so as to minimize either 40 or 40. |
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 | (3)), with one term for each classifier. |
This paper conducted research in the area of automatic paraphrase discovery. | 0 | For example, in the phrase âCompany-A last week purchased rival Marshalls from Company-Bâ, the purchased company is Marshalls, not Company-B. |
The resulting model is compact, efficiently learnable and linguistically expressive. | 0 | i=1 (f,v)âWi |
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 as those produced by Context-Free Grammars. | 0 | We use Alternating Turing Machines (Chandra, Kozen, and Stockmeyer, 1981) to show that polynomial time recognition is possible for the languages discussed in Section 4.3. |
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 | Finally, a DempsterShafer probabilistic model evaluates the evidence provided by the knowledge sources for all candidate antecedents and makes the final resolution decision. |
Human judges also pointed out difficulties with the evaluation of long sentences. | 0 | Microsoft’s approach uses dependency trees, others use hierarchical phrase models. |
This paper discusses the Potsdam Commentary Corpus, a corpus of german assembeled by potsdam university. | 0 | annotation guidelines that tell annotators what to do in case of doubt. |
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 as those produced by Context-Free Grammars. | 0 | The string pumping lemma for CFG's (uvwxy-theorem) can be seen as a corollary of this lemma. from this pumping lemma: a single path can be pumped independently. |
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 final strong hypothesis, denoted 1(x), is then the sign of a weighted sum of the weak hypotheses, 1(x) = sign (Vii atht(x)), where the weights at are determined during the run of the algorithm, as we describe below. |
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 Input: {(x1,i, Initialize: Vi, j : e(xi) = 0. |
Nevertheless, only a part of this corpus (10 texts), which the authors name "core corpus", is annotated with all this information. | 0 | That is, we can use the discourse parser on PCC texts, emulating for instance a âco-reference oracleâ that adds the information from our co-reference annotations. |
This paper presents methods to query N-gram language models, minimizing time and space costs. | 0 | Several methods exist to handle collisions; we use linear probing because it has less memory overhead when entries are small. |
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 | For this experiment, we compare our model with the uniform tag assignment prior (1TW) with the learned prior (+PRIOR). |
Due to many similarly performing systems, they are not able to draw strong conclusions on the question of correlation of manual and automatic evaluation metrics. | 0 | About half of the participants of last year’s shared task participated again. |
Nevertheless, only a part of this corpus (10 texts), which the authors name "core corpus", is annotated with all this information. | 0 | What ought to be developed now is an annotation tool that can make use of the format, allow for underspecified annotations and visualize them accordingly. |
They have made use of local and global features to deal with the instances of same token in a document. | 0 | Such constraints are derived from training data, expressing some relationship between features and outcome. |
This paper talks about Pseudo-Projective Dependency Parsing. | 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. |
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 graph propagation, the hyperparameter v was set to 2 x 10−6 and was not tuned. |
Using less training data than other systems, their NER can perform as well as other state-of-the-art NERs. | 0 | of Tokens No. |
The bias of automatic methods in favour of statistical systems seems to be less pronounced on out-of-domain test data. | 0 | Annotators argued for the importance of having correct and even multiple references. |
The problem of coreference resolution has received considerable attention, including theoretical discourse models and supervised machine learning systems. | 0 | Several coreference resolvers have used supervised learning techniques, such as decision trees and rule learners (Aone and Bennett, 1995; McCarthy and Lehnert, 1995; Ng and Cardie, 2002; Soon et al., 2001). |
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