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This paper offers a broad insight into of Arabic constituency parsing by analyzing the interplay of linguistic phenomena, annotation choices, and model design. | 0 | 95 B a s e li n e ( S e lf t a g ) 70 a l l B i k e l ( v 1 . 2 ) B a s e l i n e ( P r e t a g ) 7 0 a l l G o l d P O S 70 0.7 70 0.801 278 0.7 52 0.794 278 0.7 71 0.804 295 0.7 52 0.796 295 0.7 75 0.808 309 77. |
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 showed that any system defined in this way can be recognized in polynomial time. |
It is annotated with several data: morphology, syntax, rhetorical structure, connectors, correference and informative structure. | 0 | Unexpectedly, because the ministries of treasury and education both had prepared the teacher plan together. |
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 | The errors shown are from the Berkeley parser output, but they are representative of the other two parsing models. |
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 | Therefore, the number of fine tags varied across languages for our experiments; however, one could as well have fixed the set of HMM states to be a constant across languages, and created one mapping to the universal POS tagset. |
Evaluation was done automatically using the BLEU score and manually on fluency and adequacy. | 0 | The results of the manual and automatic evaluation of the participating system translations is detailed in the figures at the end of this paper. |
However, using the top-level semantic classes of WordNet proved to be problematic as the class distinctions are too coarse. | 0 | Its correct antecedent is âa revolverâ, which is extracted by the caseframe âkilled with <NP>â. |
The use of global features has shown excellent result in the performance on MUC-6 and MUC-7 test data. | 0 | Previous work deals with this problem by correcting inconsistencies between the named entity classes assigned to different occurrences of the same entity (Borthwick, 1999; Mikheev et al., 1998). |
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 | For example, if CFLex determines that the log- likelihood statistic for the co-occurrence of a particular noun and caseframe corresponds to the 90% confidence level, then CFLex returns .90 as its belief that the anaphor and candidate are coreferent. |
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 | In any event, to date, we have not compared different methods for deriving the set of initial frequency estimates. |
In this paper the authors present a stochastic finite-state model for segmenting Chinese text into words. | 0 | Examples are given in Table 4. |
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 | Thus corresponding pseudo-labels for instances on which gj abstain are set to zero and these instances do not contribute to the objective function. |
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 | 4. |
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 | We simulate lexical constraints by using an external lexical resource against which we verify whether OOV segments are in fact valid Hebrew lexemes. |
The approach assumes that the word reordering is restricted to a few positions in the source sentence. | 0 | The alignment mapping is j ! i = aj from source position j to target position i = aj . The use of this alignment model raises major problems if a source word has to be aligned to several target words, e.g. when translating German compound nouns. |
Using less training data than other systems, their NER can perform as well as other state-of-the-art NERs. | 0 | (2) Description Source Location Names http://www.timeanddate.com http://www.cityguide.travel-guides.com http://www.worldtravelguide.net Corporate Names http://www.fmlx.com Person First Names http://www.census.gov/genealogy/names Person Last Names Table 2: Sources of Dictionaries The McCann family . . . |
The AdaBoost algorithm was developed for supervised learning. | 0 | For a description of the application of AdaBoost to various NLP problems see the paper by Abney, Schapire, and Singer in this volume. |
Here we present two algorithms. | 0 | The second modification is more important, and is discussed in the next section. |
The use of global features has shown excellent result in the performance on MUC-6 and MUC-7 test data. | 0 | However, such an approach requires a number of hand-coded systems, which may not be available in languages other than English. |
Two general approaches are presented and two combination techniques are described for each approach. | 0 | Both authors are members of the Center for Language and Speech Processing at Johns Hopkins University. |
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 | We develop our POS induction model based on the feature-based HMM of Berg-Kirkpatrick et al. (2010). |
The approach has been successfully tested on the 8 000-word Verbmobil task. | 0 | In Section 3, we introduce our novel concept to word reordering and a DP-based search, which is especially suitable for the translation direction from German to English. |
Each out-of-domain phrase pair was characterized by a set of simple features intended to reflect how useful it would be. | 0 | The features are weighted within a logistic model to give an overall weight that is applied to the phrase pair’s frequency prior to making MAP-smoothed relative-frequency estimates (different weights are learned for each conditioning direction). |
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 | Table 8b shows that verbal nouns are the hardest pre-terminal categories to identify. |
This paper discusses the Potsdam Commentary Corpus, a corpus of german assembeled by potsdam university. | 0 | Annotation of syntactic structure for the core corpus has just begun. |
This paper presents methods to query N-gram language models, minimizing time and space costs. | 0 | RandLM’s stupid backoff variant stores counts instead of probabilities and backoffs. |
This paper presents methods to query N-gram language models, minimizing time and space costs. | 0 | Tokens were converted to vocabulary identifiers in advance and state was carried from each query to the next. |
The authors believe automatic paraphrase discovery is an important component for building a fully automatic information extraction system. | 0 | The basic strategy is, for a given pair of entity types, to start with some examples, like several famous book title and author pairs; and find expressions which contains those names; then using the found expressions, find more author and book title pairs. |
The model incorporates various recent techniques for incorporating and manipulating linguistic knowledge using finite-state transducers. | 0 | The major problem for our seg menter, as for all segmenters, remains the problem of unknown words (see Fung and Wu [1994]). |
The three parsers were trained and tuned by their creators on various sections of the WSJ portion of the Penn Treebank. | 0 | This is not an oversight. |
This topic has been getting more attention, driven by the needs of various NLP applications. | 0 | In order to solve this problem, a parse tree is needed to understand that âLotusâ is not the object of âestimatesâ. |
they evaluate various specific aspects of the segmentation, as well as the overall segmentation performance. | 0 | However, until such standards are universally adopted in evaluating Chinese segmenters, claims about performance in terms of simple measures like percent correct should be taken with a grain of salt; see, again, Wu and Fung (1994) for further arguments supporting this conclusion. |
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 method reported in this paper makes use solely of unigram probabilities, and is therefore a zeroeth-order model: the cost of a particular segmentation is estimated as the sum of the costs of the individual words in the segmentation. |
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 | The second setting uses the news-related subcorpora for the NIST09 MT Chinese to English evaluation8 as IN, and the remaining NIST parallel Chinese/English corpora (UN, Hong Kong Laws, and Hong Kong Hansard) as OUT. |
A beam search concept is applied as in speech recognition. | 0 | Input: Ja , wunderbar . Konnen wir machen . MonS: Yes, wonderful. |
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 | In addition we report for each model its performance on goldsegmented input (GS) to indicate the upper bound 11Overt definiteness errors may be seen as a wrong feature rather than as wrong constituent and it is by now an accepted standard to report accuracy with and without such errors. for the grammars’ performance on the parsing task. |
There is no global pruning. | 0 | In. |
The authors in this paper describe a search procedure for statistical machine translation (MT) based on dynamic programming (DP). | 0 | (1), Pr(eI 1) is the language model, which is a trigram language model in this case. |
The authors show that PATB is similar to other tree-banks but that annotation consistency remains low. | 0 | Table 8a shows that the best model recovers SBAR at only 71.0% F1. |
This paper presents methods to query N-gram language models, minimizing time and space costs. | 0 | We allow any number of bits from 2 to 25, unlike IRSTLM (8 bits) and BerkeleyLM (17−20 bits). |
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 | Second, we treat the projected labels as features in an unsupervised model (§5), rather than using them directly for supervised training. |
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 | Our method does not assume any knowledge about the target language (in particular no tagging dictionary is assumed), making it applicable to a wide array of resource-poor languages. |
The experimental tests are carried out on the Verbmobil task which is a limited-domain spoken-language task. | 0 | The alignment mapping is j ! i = aj from source position j to target position i = aj . The use of this alignment model raises major problems if a source word has to be aligned to several target words, e.g. when translating German compound nouns. |
The second algorithm builds on a boosting algorithm called AdaBoost. | 0 | The input to AdaBoost is a set of training examples ((xi , yi), , (x„.„ yrn)). |
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 | 2. |
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 | For example, kidnapping victims should be extracted from the subject of the verb âkidnappedâ when it occurs in the passive voice (the shorthand representation of this pattern would be â<subject> were kidnappedâ). |
They have made use of local and global features to deal with the instances of same token in a document. | 0 | We will show that by giving the first model some global features, MENERGI outperforms Borthwick' s reference resolution classifier. |
This paper conducted research in the area of automatic paraphrase discovery. | 0 | If the expression is a word or a short phrase (like âcorporationâ and âcompanyâ), it is called a âsynonymâ. |
We chose one of four labels for each example: location, person, organization, or noise where the noise category was used for items that were outside the three categories. | 0 | The unlabeled data gives many such "hints" that two features should predict the same label, and these hints turn out to be surprisingly useful when building a classifier. |
Human judges also pointed out difficulties with the evaluation of long sentences. | 0 | We are therefore applying a different method, which has been used at the 2005 DARPA/NIST evaluation. |
However, these approaches are ill-equipped to directly represent type-based constraints such as sparsity. | 0 | Specifically, for both settings we report results on the median run for each setting. |
We chose one of four labels for each example: location, person, organization, or noise where the noise category was used for items that were outside the three categories. | 0 | This intuition is born out by the experimental results. |
They proposed a single joint model for performing both morphological segmentation and syntactic disambiguation which bypasses the associated circularity. | 0 | Secondly, for all our models we provide better fine- and coarse-grained POS-tagging accuracy, and all pruned models outperform the Oracle results reported by them.12 In terms of syntactic disambiguation, even the simplest grammar pruned with HSPELL outperforms their non-Oracle results. |
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 | La ng ua ge # To ke ns # W or d Ty pe s # Ta gs E ng lis h D a ni s h D u tc h G e r m a n P or tu g u e s e S p a ni s h S w e di s h 1 1 7 3 7 6 6 9 4 3 8 6 2 0 3 5 6 8 6 9 9 6 0 5 2 0 6 6 7 8 8 9 3 3 4 1 9 1 4 6 7 4 9 2 0 6 1 8 3 5 6 2 8 3 9 3 7 2 3 2 5 2 8 9 3 1 1 6 4 5 8 2 0 0 5 7 4 5 2 5 1 2 5 4 2 2 4 7 4 1 Table 2: Statistics for various corpora utilized in experiments. |
Here we present two algorithms. | 0 | Each unlabeled pair (x1,i, x2,i) is represented as an edge between nodes corresponding to x1,i and X2,i in the graph. |
They showed the efficacy of graph-based label propagation for projecting part-of-speech information across languages. | 0 | As indicated by bolding, for seven out of eight languages the improvements of the “With LP” setting are statistically significant with respect to the other models, including the “No LP” setting.11 Overall, it performs 10.4% better than the hitherto state-of-the-art feature-HMM baseline, and 4.6% better than direct projection, when we macro-average the accuracy over all languages. |
All the texts were annotated by two people. | 0 | This is manifest in the lexical choices but 1 www.coli.unisb.de/â¼thorsten/tnt/ Dagmar Ziegler is up to her neck in debt. |
This paper presents methods to query N-gram language models, minimizing time and space costs. | 0 | Adam Pauls provided a pre-release comparison to BerkeleyLM and an initial Java interface. |
The model incorporates various recent techniques for incorporating and manipulating linguistic knowledge using finite-state transducers. | 0 | We further thank Dr. J.-S. |
Human judges also pointed out difficulties with the evaluation of long sentences. | 0 | Often, two systems can not be distinguished with a confidence of over 95%, so there are ranked the same. |
They focused on phrases which two Named Entities, and proceed in two stages. | 0 | The procedure using the tagged sentences to discover paraphrases takes about one hour on a 2GHz Pentium 4 PC with 1GB of memory. |
BABAR's performance in both domains of terrorism and natural disaster, and the contextual-role knowledge in pronouns have shown successful results. | 0 | Since pronouns carry little semantics of their own, resolving them depends almost entirely on context. |
Other kinds of productive word classes, such as company names, abbreviations,and place names can easily be handled given appropriate models. | 0 | This WFST represents the segmentation of the text into the words AB and CD, word boundaries being marked by arcs mapping between f and part-of-speech labels. |
It is probably the first analysis of Arabic parsing of this kind. | 0 | Second, we show that although the Penn Arabic Treebank is similar to other tree- banks in gross statistical terms, annotation consistency remains problematic. |
They plan on extending instance-weighting to other standard SMT components and capture the degree of generality of phrase pairs. | 0 | The dev and test sets were randomly chosen from the EMEA corpus. |
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 | SRILM’s compact variant has an incredibly expensive destructor, dwarfing the time it takes to perform translation, and so we also modified Moses to avoiding the destructor by calling exit instead of returning normally. |
Their work is closely related to recent approaches that incorporate the sparsity constraint into the POS induction process. | 0 | Part-of-speech (POS) tag distributions are known to exhibit sparsity â a word is likely to take a single predominant tag in a corpus. |
The experimental tests are carried out on the Verbmobil task which is a limited-domain spoken-language task. | 0 | In this section, we brie y review our translation approach. |
The overall parsing accuracy obtained with the pseudo-projective approach is still lower than for the best projective parsers. | 0 | As shown in Table 3, the proportion of sentences containing some non-projective dependency ranges from about 15% in DDT to almost 25% in PDT. |
the "Potsdam Commentary Corpus" or PCC consists of 170 commentaries from Ma¨rkische Allgemeine Zeitung, a German regional daily. | 0 | When the signal is a coordinating conjunction, the second span is usually the clause following the conjunction; the first span is often the clause preceding it, but sometimes stretches further back. |
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 | We first make use of our morphological analyzer to find all segmentation possibilities by chopping off all prefix sequence possibilities (including the empty prefix) and construct a lattice off of them. |
Their work is closely related to recent approaches that incorporate the sparsity constraint into the POS induction process. | 0 | (2009). |
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 | (2010) reports the best unsupervised results for English. |
This paper discusses the Potsdam Commentary Corpus, a corpus of german assembeled by potsdam university. | 0 | Trying to integrate constituent ordering and choice of referring expressions, (Chiarcos 2003) developed a numerical model of salience propagation that captures various factors of authorâs intentions and of information structure for ordering sentences as well as smaller constituents, and picking appropriate referring expressions.10 Chiarcos used the PCC annotations of co-reference and information structure to compute his numerical models for salience projection across the generated texts. |
Evaluation was done automatically using the BLEU score and manually on fluency and adequacy. | 0 | For instance, for out-ofdomain English-French, Systran has the best BLEU and manual scores. |
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 | In contrast to the Bayesian HMM, θt is not drawn from a distribution which has support for each of the n word types. |
This paper presents a maximum entropy-based named entity recognizer (NER). | 0 | The system will then look for sequences of initial capitalized words that match the acronyms found in the whole document. |
The texts were annotated with the RSTtool. | 0 | We follow the guidelines developed in the TIGER project (Brants et al. 2002) for syntactic annotation of German newspaper text, using the Annotate3 tool for interactive construction of tree structures. |
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 | Another way to interpret this is that less than 5% of the correct constituents are missing from the hypotheses generated by the union of the three parsers. |
The problem of coreference resolution has received considerable attention, including theoretical discourse models and supervised machine learning systems. | 0 | Tables 4 and 5 also show that putting all of the contextual role KSs in play at the same time produces the greatest performance gain. |
The approach has been successfully tested on the 8 000-word Verbmobil task. | 0 | Covering the first uncovered position in the source sentence, we use the language model probability p(ej$; $). |
Here both parametric and non-parametric models are explored. | 0 | The results of this experiment can be seen in Table 5. |
This assumption, however, is not inherent to type-based tagging models. | 0 | Learned Tag Prior (PRIOR) We next assume there exists a single prior distribution Ï over tag assignments drawn from DIRICHLET(β, K ). |
The problem of coreference resolution has received considerable attention, including theoretical discourse models and supervised machine learning systems. | 0 | For definite NPs, the results are a mixed bag: some knowledge sources increased recall a little, but at the expense of some precision. |
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 | The availability of these resources guided our selection of foreign languages. |
The resulting model is compact, efficiently learnable and linguistically expressive. | 0 | The second row represents the performance of the median hyperparameter setting. |
The corpus was annoted with different linguitic information. | 0 | For developing these mechanisms, the possibility to feed in hand-annotated information is very useful. |
There is no global pruning. | 0 | This approach leads to a search procedure with complexity O(E3 J4). |
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 | The scores and confidence intervals are detailed first in the Figures 7–10 in table form (including ranks), and then in graphical form in Figures 11–16. |
This paper conducted research in the area of automatic paraphrase discovery. | 0 | Now we have sets of phrases which share a keyword and we have links between those sets. |
The problem of coreference resolution has received considerable attention, including theoretical discourse models and supervised machine learning systems. | 0 | We combined evidence from four contextual role knowledge sources with evidence from seven general knowledge sources using a DempsterShafer probabilistic model. |
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 | Denote the unthresholded classifiers after t — 1 rounds by git—1 and assume that it is the turn for the first classifier to be updated while the second one is kept fixed. |
Here we present two algorithms. | 0 | Thus an explicit assumption about the redundancy of the features — that either the spelling or context alone should be sufficient to build a classifier — has been built into the algorithm. |
While many systems had similar performance, the results offered interesting insights, especially, about the relative performance of statistical and rule-based systems. | 0 | For instance, in the recent IWSLT evaluation, first fluency annotations were solicited (while withholding the source sentence), and then adequacy annotations. |
Two general approaches are presented and two combination techniques are described for each approach. | 0 | None of the models we have presented utilize features associated with a particular constituent (i.e. the label, span, parent label, etc.) to influence parser preference. |
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 | Only one of the first n positions which are not already aligned in a partial hypothesis may be chosen, where n is set to 4. |
This corpus has several advantages: it is annotated at different levels. | 0 | (Carlson, Marcu 2001) responded to this situation with relatively precise (and therefore long!) |
All the texts were annotated by two people. | 0 | structure Besides the applications just sketched, the over- arching goal of developing the PCC is to build up an empirical basis for investigating phenomena of discourse structure. |
This paper presents methods to query N-gram language models, minimizing time and space costs. | 0 | Queries take the form p(wn|wn−1 1 ) where wn1 is an n-gram. |
The problem of coreference resolution has received considerable attention, including theoretical discourse models and supervised machine learning systems. | 0 | In this section, we describe the seven general knowledge sources and explain how the DempsterShafer model makes resolutions. |
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