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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 | We hope that this will allow practitioners to apply our approach directly to languages for which no resources are available. |
The authors show that PATB is similar to other tree-banks but that annotation consistency remains low. | 0 | In the initial release of the ATB, inter-annotator agreement was inferior to other LDC treebanks (Maamouri et al., 2008). |
Using less training data than other systems, their NER can perform as well as other state-of-the-art NERs. | 0 | In IdentiFinder, there is a priority in the feature assignment, such that if one feature is used for a token, another feature lower in priority will not be used. |
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 | Of these cases, 38 were temporal expressions (either a day of the week or month of the year). |
The first method builds on results from (Yarowsky 95) and (Blum and Mitchell 98). | 0 | From here on we will refer to the named-entity string itself as the spelling of the entity, and the contextual predicate as the context. |
They incorporated instance-weighting into a mixture-model framework, and found that it yielded consistent improvements over a wide range of baselines. | 0 | This is a simple and effective alternative to setting weights discriminatively to maximize a metric such as BLEU. |
It is well-known that English constituency parsing models do not generalize to other languages and treebanks. | 0 | All three curves remain steep at the maximum training set size of 18818 trees. |
This paper presents methods to query N-gram language models, minimizing time and space costs. | 0 | Our implementation permits jumping to any n-gram of any length with a single lookup; this appears to be unique among language model implementations. |
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. | 1 | In this work, we take a more direct approach and treat a word type and its allowed POS tags as a primary element of the model. |
This paper offers a broad insight into of Arabic constituency parsing by analyzing the interplay of linguistic phenomena, annotation choices, and model design. | 0 | 43 80. |
The problem of coreference resolution has received considerable attention, including theoretical discourse models and supervised machine learning systems. | 0 | Figure 3 shows examples of semantic expectations that were learned. |
It is well-known that English constituency parsing models do not generalize to other languages and treebanks. | 0 | Lattice parsing (Chappelier et al., 1999) is an alternative to a pipeline that prevents cascading errors by placing all segmentation options into the parse chart. |
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 | Daum´e (2007) applies a related idea in a simpler way, by splitting features into general and domain-specific versions. |
This paper presents a maximum entropy-based named entity recognizer (NER). | 0 | Previous work that involves the gathering of information from the whole document often uses a secondary classifier, which corrects the mistakes of a primary sentence- based classifier. |
It also incorporates the Good-Turing methodin estimating the likelihoods of previously unseen constructions, including morphological derivatives and personal names. | 0 | Similarly, there is no compelling evidence that either of the syllables of f.ifflll binllang2 'betelnut' represents a morpheme, since neither can occur in any context without the other: more likely fjfflll binllang2 is a disyllabic morpheme. |
Here we show how non-projective dependency parsing can be achieved by combining a data driven projective parser with special graph transformation techniques. | 0 | Finally, since non-projective constructions often involve long-distance dependencies, the problem is closely related to the recovery of empty categories and non-local dependencies in constituency-based parsing (Johnson, 2002; Dienes and Dubey, 2003; Jijkoun and de Rijke, 2004; Cahill et al., 2004; Levy and Manning, 200... |
Using less training data than other systems, their NER can perform as well as other state-of-the-art NERs. | 0 | In the maximum entropy framework, there is no such constraint. |
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 | termined by the category of the word that follows it. |
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 | We currently simulate this by crafting a WCFG and feeding it to BitPar. |
They have made use of local and global features to deal with the instances of same token in a document. | 0 | Borth 2MUC data can be obtained from the Linguistic Data Consortium: http://www.ldc.upenn.edu 3Training data for IdentiFinder is actually given in words (i.e., 650K & 790K words), rather than tokens Table 6: Comparison of results for MUC7 wick (1999) reported using dictionaries of person first names, corporate names an... |
The PROBING data structure uses linear probing hash tables and is designed for speed. | 0 | Many packages perform language model queries. |
Other kinds of productive word classes, such as company names, abbreviations,and place names can easily be handled given appropriate models. | 0 | The second weakness is purely conceptual, and probably does not affect the per formance of the model. |
This paper talks about Pseudo-Projective Dependency Parsing. | 0 | As can be seen from the last column in Table 1, both Head and Head+Path may theoretically lead to a quadratic increase in the number of distinct arc labels (Head+Path being worse than Head only by a constant factor), while the increase is only linear in the case of Path. |
The authors cluster NE instance pairs based on the words in the context using bag-of-words methods. | 0 | In order to solve this problem, a parse tree is needed to understand that âLotusâ is not the object of âestimatesâ. |
Nevertheless, only a part of this corpus (10 texts), which the authors name "core corpus", is annotated with all this information. | 0 | annotation guidelines that tell annotators what to do in case of doubt. |
This paper presents a maximum entropy-based named entity recognizer (NER). | 0 | of Articles No. |
It is probably the first analysis of Arabic parsing of this kind. | 0 | Annotation consistency is important in any supervised learning task. |
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 POS distributions over the foreign trigram types are used as features to learn a better unsupervised POS tagger (§5). |
The three parsers were trained and tuned by their creators on various sections of the WSJ portion of the Penn Treebank. | 0 | The resulting parsers surpass the best previously published performance results for the Penn Treebank. |
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 | (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. |
The TRIE model uses less memory than the smallest lossless alternative and is still faster than SRILM. | 0 | 0750271 and by the DARPA GALE program. |
The TRIE model uses less memory than the smallest lossless alternative and is still faster than SRILM. | 0 | For speed, we plan to implement the direct-mapped cache from BerkeleyLM. |
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 | However, there is again local grammatical information that should favor the split in the case of (1a): both .ma3 'horse' and .ma3 lu4 are nouns, but only .ma3 is consistent with the classifier pil, the classifier for horses.21 By a similar argument, the preference for not splitting , lm could be strengthened in (lb) by... |
It is annotated with several data: morphology, syntax, rhetorical structure, connectors, correference and informative structure. | 0 | We use MMAX for this annotation as well. |
Foster et all describe a new approach to SMT adaptation that weights out-of-domain phrase pairs according to their relevance to the target domain, determined by both how similar to it they appear to be, and whether they belong to general language or not. | 0 | Sentence pairs are the natural instances for SMT, but sentences often contain a mix of domain-specific and general language. |
This paper talks about Unsupervised Models for Named Entity Classification. | 0 | Supervised methods have been applied quite successfully to the full MUC named-entity task (Bikel et al. 97). |
Using less training data than other systems, their NER can perform as well as other state-of-the-art NERs. | 0 | (1998) have also used a maximum entropy classifier that uses already tagged entities to help tag other entities. |
They proposed a single joint model for performing both morphological segmentation and syntactic disambiguation which bypasses the associated circularity. | 0 | This supports our main thesis that decisions taken by single, improved, grammar are beneficial for both tasks. |
The authors cluster NE instance pairs based on the words in the context using bag-of-words methods. | 0 | It is a relatively frequent word in the domain, but it can be used in different extraction scenarios. |
This topic has been getting more attention, driven by the needs of various NLP applications. | 0 | The links can solve the problem. |
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 | As can be seen from the last column in Table 1, both Head and Head+Path may theoretically lead to a quadratic increase in the number of distinct arc labels (Head+Path being worse than Head only by a constant factor), while the increase is only linear in the case of Path. |
There is no global pruning. | 0 | We have tested the translation system on the Verbmobil task (Wahlster 1993). |
A beam search concept is applied as in speech recognition. | 0 | An extended lexicon model is defined, and its likelihood is compared to a baseline lexicon model, which takes only single-word dependencies into account. |
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 | This fully generative model caters for real interaction between the syntactic and morphological levels as a part of a single coherent process. |
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 following two error criteria are used in our experiments: mWER: multi-reference WER: We use the Levenshtein distance between the automatic translation and several reference translations as a measure of the translation errors. |
This paper talks about Pseudo-Projective Dependency Parsing. | 0 | Formally, we define dependency graphs as follows: 3. |
The model incorporates various recent techniques for incorporating and manipulating linguistic knowledge using finite-state transducers. | 0 | pronunciation depends upon word affiliation: tfJ is pronounced deO when it is a prenominal modification marker, but di4 in the word §tfJ mu4di4 'goal'; fl; is normally ganl 'dry,' but qian2 in a person's given name. |
On the basis of that observation, they described a class of formalisms which they called Linear Context- Free Rewriting Systems (LCFRs), and showed they were recognizable in polynomial time and generated only semilinear languages. | 0 | TAG's can be shown to be equivalent to this restricted system. |
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 model is often further restricted so that each source word is assigned to exactly one target word (Brown et al., 1993; Ney et al., 2000). |
The texts were annotated with the RSTtool. | 0 | Commentaries argue in favor of a specific point of view toward some political issue, often dicussing yet dismissing other points of view; therefore, they typically offer a more interesting rhetorical structure than, say, narrative text or other portions of newspapers. |
It also incorporates the Good-Turing methodin estimating the likelihoods of previously unseen constructions, including morphological derivatives and personal names. | 0 | Approaches differ in the algorithms used for scoring and selecting the best path, as well as in the amount of contextual information used in the scoring process. |
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 | Papers that use this method or minor variants thereof include Liang (1986), Li et al. |
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 | All features were conjoined with the state z. |
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 points enumerated above are particularly related to ITS, but analogous arguments can easily be given for other applications; see for example Wu and Tseng's (1993) discussion of the role of segmentation in information retrieval. |
The texts were annotated with the RSTtool. | 0 | The domains are the linguistic spans that are to receive an IS-partitioning, and the units are the (smaller) spans that can play a role as a constituent of such a partitioning. |
Most IE researchers have been creating paraphrase knowledge by hand and specific tasks. | 0 | For each pair we also record the context, i.e. the phrase between the two NEs (Step1). |
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 | âThe gunâ will be extracted by the caseframe âfired <patient>â. |
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 | There are two possible reasons: (1) the knowledge sources are resolving different cases of anaphora, and (2) the knowledge sources provide multiple pieces of evidence in support of (or against) a candidate, thereby acting synergistically to push the DempsterShafer model over the belief threshold in favor of a single ca... |
Using less training data than other systems, their NER can perform as well as other state-of-the-art NERs. | 0 | IdentiFinder ' 99' s results are considerably better than IdentiFinder ' 97' s. IdentiFinder' s performance in MUC7 is published in (Miller et al., 1998). |
They plan on extending instance-weighting to other standard SMT components and capture the degree of generality of phrase pairs. | 0 | The idea of distinguishing between general and domain-specific examples is due to Daum´e and Marcu (2006), who used a maximum-entropy model with latent variables to capture the degree of specificity. |
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 | By aggregating the POS labels of the English tokens to types, we can generate label distributions for the English vertices. |
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 | For all grammars, we use fine-grained PoS tags indicating various morphological features annotated therein. |
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 | This group contains a large number of features (one for each token string present in the training data). |
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 | (2009). |
The use of global features has shown excellent result in the performance on MUC-6 and MUC-7 test data. | 0 | Named Entity Recognition: A Maximum Entropy Approach Using Global Information |
There are clustering approaches that assign a single POS tag to each word type. | 0 | This line of work has been motivated by empirical findings that the standard EM-learned unsupervised HMM does not exhibit sufficient word tag sparsity. |
The PROBING data structure uses linear probing hash tables and is designed for speed. | 0 | Memory mapping also allows the same model to be shared across processes on the same machine. |
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 confidence intervals are computed by bootstrap resampling for BLEU, and by standard significance testing for the manual scores, as described earlier in the paper. |
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 | shortest match at each point. |
they evaluate various specific aspects of the segmentation, as well as the overall segmentation performance. | 0 | Another question that remains unanswered is to what extent the linguistic information he considers can be handled-or at least approximated-by finite-state language models, and therefore could be directly interfaced with the segmentation model that we have presented in this paper. |
However, using the top-level semantic classes of WordNet proved to be problematic as the class distinctions are too coarse. | 0 | Training examples are generated automatically by identifying noun phrases that can be easily resolved with their antecedents using lexical and syntactic heuristics. |
The manual evaluation of scoring translation on a graded scale from 1â5 seems to be very hard to perform. | 0 | Annotators argued for the importance of having correct and even multiple references. |
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 X and Y are coreferent, then both X and Y are considered to co-occur with the caseframe that extracts X as well as the caseframe that extracts Y. We will refer to the set of nouns that co-occur with a caseframe as the lexical expectations of the case- frame. |
This paper presents a maximum entropy-based named entity recognizer (NER). | 0 | Out-of-Vocabulary: We derived a lexicon list from WordNet 1.6, and words that are not found in this list have a feature out-of-vocabulary set to 1. |
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 | The Berkeley parser gives state-of-the-art performance for all metrics. |
Their work is closely related to recent approaches that incorporate the sparsity constraint into the POS induction process. | 0 | This design does not guarantee âstructural zeros,â but biases towards sparsity. |
The authors show that PATB is similar to other tree-banks but that annotation consistency remains low. | 0 | This feature includes named entities, which the ATB marks with a flat NP node dominating an arbitrary number of NNP pre-terminal daughters (Figure 2). |
This paper talks about Unsupervised Models for Named Entity Classification. | 0 | (Hearst 92) describes a method for extracting hyponyms from a corpus (pairs of words in "isa" relations). |
These clusters are computed using an SVD variant without relying on transitional structure. | 0 | The tokens w are generated by token-level tags t from an HMM parameterized by the lexicon structure. |
They used graph-based label propagation for cross-lingual knowledge transfer and used the projected labels as features in an unsupervised model. | 0 | It falls short of the “Projection” baseline for German, but is statistically indistinguishable in terms of accuracy. |
They showed the efficacy of graph-based label propagation for projecting part-of-speech information across languages. | 0 | We use label propagation in two stages to generate soft labels on all the vertices in the graph. |
This paper offers a broad insight into of Arabic constituency parsing by analyzing the interplay of linguistic phenomena, annotation choices, and model design. | 0 | (a) Of the high frequency phrasal categories, ADJP and SBAR are the hardest to parse. |
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 | Our smoothing procedure takes into account all the aforementioned aspects and works as follows. |
Here we present two algorithms. | 0 | The CoBoost algorithm described above divides the function Zco into two parts: Zco = 40 + 40. |
This paper talks about KenLM: Faster and Smaller Language Model Queries. | 0 | Each trie node is individually allocated and full 64-bit pointers are used to find them, wasting memory. |
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 | The details are given in (Och and Ney, 2000). |
Replacing this with a ranked evaluation seems to be more suitable. | 0 | Not every annotator was fluent in both the source and the target language. |
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 | A greedy algorithm (or maximum-matching algorithm), GR: proceed through the sentence, taking the longest match with a dictionary entry at each point. |
It also incorporates the Good-Turing methodin estimating the likelihoods of previously unseen constructions, including morphological derivatives and personal names. | 0 | The model described here thus demonstrates great potential for use in widespread applications. |
Human judges also pointed out difficulties with the evaluation of long sentences. | 0 | Manual and Automatic Evaluation of Machine Translation between European Languages |
This paper discusses the Potsdam Commentary Corpus, a corpus of german assembeled by potsdam university. | 0 | And indeed, converging on annotation guidelines is even more difficult than it is with co-reference. |
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 | Finally, quite a few hanzi are homographs, meaning that they may be pronounced in several different ways, and in extreme cases apparently represent different morphemes: The prenominal modifi cation marker eg deO is presumably a different morpheme from the second morpheme of §eg mu4di4, even though they are written t... |
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 terrorism, BABAR generated 5,078 resolutions: 2,386 from lexical seeding and 2,692 from syntactic seeding. |
It is annotated with several data: morphology, syntax, rhetorical structure, connectors, correference and informative structure. | 0 | The web-based Annis imports data in a variety of XML formats and tagsets and displays it in a tier-orientedway (optionally, trees can be drawn more ele gantly in a separate window). |
They proposed an unsupervised method to discover paraphrases from a large untagged corpus. | 0 | We have checked if there are similar verbs in other major domains, but this was the only one. |
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 | 86 78. |
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 | Our new approach, which is called quasi-monotone search, processes the source sentence monotonically, while explicitly taking into account the positions of the German verbgroup. |
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 | Note that because we extracted only high-confidence alignments, many foreign vertices will not be connected to any English vertices. |
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 | These are written to the state s(wn1) and returned so that they can be used for the following query. |
They proposed an unsupervised method to discover paraphrases from a large untagged corpus. | 0 | However, those methods need initial seeds, so the relation between entities has to be known in advance. |
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