source_text
stringlengths 27
368
| label
int64 0
1
| target_text
stringlengths 1
5.38k
|
|---|---|---|
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 | German city names are replaced by category markers. |
BABAR's performance in both domains of terrorism and natural disaster, and the contextual-role knowledge in pronouns have shown successful results. | 0 | For each domain, we created a semantic dictionary by doing two things. |
Their work is closely related to recent approaches that incorporate the sparsity constraint into the POS induction process. | 0 | 8 1 2. |
The contextual rules are restricted and may not be applicable to every example, but the spelling rules are generally applicable and should have good coverage. | 0 | Thus at each iteration the algorithm is forced to pick features for the location, person and organization in turn for the classifier being trained. |
The AdaBoost algorithm was developed for supervised learning. | 0 | One implementation issue deserves some elaboration. |
The TRIE model uses less memory than the smallest lossless alternative and is still faster than SRILM. | 0 | Language models are widely applied in natural language processing, and applications such as machine translation make very frequent queries. |
Here both parametric and non-parametric models are explored. | 0 | This is not an oversight. |
This paper talks about Unsupervised Models for Named Entity Classification. | 0 | The input to AdaBoost is a set of training examples ((xi , yi), , (x„.„ yrn)). |
Other kinds of productive word classes, such as company names, abbreviations,and place names can easily be handled given appropriate models. | 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 the same way.4 The second point, which will be relevant in the discussion of personal names in Section 4.4, relates to the internal structure of hanzi. |
However, using the top-level semantic classes of WordNet proved to be problematic as the class distinctions are too coarse. | 0 | If a candidate has a belief value ⥠.50, then we select that candidate as the antecedent for the anaphor. |
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 | In addition to the named-entity string (Maury Cooper or Georgia), a contextual predictor was also extracted. |
The overall parsing accuracy obtained with the pseudo-projective approach is still lower than for the best projective parsers. | 0 | More details on the memory-based prediction can be found in Nivre et al. (2004) and Nivre and Scholz (2004). |
Their method did not assume any knowledge about the target language, making it applicable to a wide array of resource-poor languages. | 0 | For each language under consideration, Petrov et al. (2011) provide a mapping A from the fine-grained language specific POS tags in the foreign treebank to the universal POS tags. |
This paper talks about Exploiting Diversity in Natural Language Processing: Combining Parsers. | 0 | We used these three parsers to explore parser combination techniques. |
They have made use of local and global features to deal with the instances of same token in a document. | 0 | Hence we decided to restrict ourselves to only information from the same document. |
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 | Moreover, the Stanford parser achieves the most exact Leaf Ancestor matches and tagging accuracy that is only 0.1% below the Bikel model, which uses pre-tagged input. |
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 | For each feature type f and tag t, a multinomial Ïtf is drawn from a symmetric Dirichlet distribution with concentration parameter β. |
While many systems had similar performance, the results offered interesting insights, especially, about the relative performance of statistical and rule-based systems. | 0 | We are currently working on a complete open source implementation of a training and decoding system, which should become available over the summer. pus, from which also the in-domain test set is taken. |
The fact that projective dependency parsers can never exactly reproduce the analyses found in non-projective tree banks is often neglected because of the relative scarcity of problematic constructions. | 0 | Thus, most broad-coverage parsers based on dependency grammar have been restricted to projective structures. |
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 | Word Re-ordering and DP-based Search in Statistical Machine Translation |
Their work is closely related to recent approaches that incorporate the sparsity constraint into the POS induction process. | 0 | (2010) reports the best unsupervised results for English. |
The authors believe automatic paraphrase discovery is an important component for building a fully automatic information extraction system. | 0 | In this domain the major scenarios involve the things they agreed on, rather than the mere fact that they agreed. |
This paper presents a maximum entropy-based named entity recognizer (NER). | 0 | In MUC6, the best result is achieved by SRA (Krupka, 1995). |
The overall parsing accuracy obtained with the pseudo-projective approach is still lower than for the best projective parsers. | 1 | The overall parsing accuracy obtained with the pseudo-projective approach is still lower than for the best projective parsers. |
The fact that projective dependency parsers can never exactly reproduce the analyses found in non-projective tree banks is often neglected because of the relative scarcity of problematic constructions. | 0 | In the present study, we limit ourselves to an algorithmic approach, using a deterministic breadthfirst search. |
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 most cases, however, these expansions come with a steep increase in model complexity, with respect to training procedure and inference time. |
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 | Our goal is to define a class of formal systems, and show that any member of this class will possess certain attractive properties. |
This paper presents a maximum entropy-based named entity recognizer (NER). | 0 | For example, in the sentence that starts with âBush put a freeze on . . . |
The authors in this paper describe a search procedure for statistical machine translation (MT) based on dynamic programming (DP). | 0 | An error count of 0:0 is assigned to a perfect translation, and an error count of 1:0 is assigned to a semantically and syntactically wrong translation. |
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 | with the number of exactly matching guess trees. |
Here we present two algorithms. | 0 | Now assume we have n pairs (xi,, x2,i) drawn from X1 X X2, where the first m pairs have labels whereas for i = m+ 1...n the pairs are unlabeled. |
This paper conducted research in the area of automatic paraphrase discovery. | 0 | We did have a problem classifying some modified noun phrases where the modified phrase does not represent a qualified or restricted form of the head, like âchairmanâ and âvice chairmanâ, as these are both represented by the keyword âchairmanâ. |
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 | Until now, all evaluations of Arabic parsingâincluding the experiments in the previous sectionâhave assumed gold segmentation. |
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 | 9 65.5 46. |
The approach has been successfully tested on the 8 000-word Verbmobil task. | 0 | A search restriction especially useful for the translation direction from German to English is presented. |
The problem of coreference resolution has received considerable attention, including theoretical discourse models and supervised machine learning systems. | 0 | Ideally weâd like to know the thematic role of each extracted noun phrase, but AutoSlog does not generate thematic roles. |
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 | It is well know that language pairs such as EnglishGerman pose more challenges to machine translation systems than language pairs such as FrenchEnglish. |
they evaluate various specific aspects of the segmentation, as well as the overall segmentation performance. | 0 | This smooth guarantees that there are no zeroes estimated. |
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 | Chang of Tsinghua University, Taiwan, R.O.C., for kindly providing us with the name corpora. |
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 task can be considered to be one component of the MUC (MUC-6, 1995) named entity task (the other task is that of segmentation, i.e., pulling possible people, places and locations from text before sending them to the classifier). |
Their work is closely related to recent approaches that incorporate the sparsity constraint into the POS induction process. | 0 | â similar results have been observed across multiple languages. |
Their work is closely related to recent approaches that incorporate the sparsity constraint into the POS induction process. | 0 | On one end of the spectrum are clustering approaches that assign a single POS tag to each word type (Schutze, 1995; Lamar et al., 2010). |
It is well-known that English constituency parsing models do not generalize to other languages and treebanks. | 0 | To differentiate between the coordinating and discourse separator functions of conjunctions (Table 3), we mark each CC with the label of its right sister (splitCC). |
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 | to explore how well we can induce POS tags using only the one-tag-per-word constraint. |
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 | 7 Big 5 is the most popular Chinese character coding standard in use in Taiwan and Hong Kong. |
The fact that projective dependency parsers can never exactly reproduce the analyses found in non-projective tree banks is often neglected because of the relative scarcity of problematic constructions. | 0 | Memory-based classifiers for the experiments were created using TiMBL (Daelemans et al., 2003). |
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 | While size of the resulting transducers may seem daunting-the segmenter described here, as it is used in the Bell Labs Mandarin TTS system has about 32,000 states and 209,000 arcs-recent work on minimization of weighted machines and transducers (cf. |
They proposed an unsupervised method to discover paraphrases from a large untagged corpus. | 0 | This remains as future work. |
The authors cluster NE instance pairs based on the words in the context using bag-of-words methods. | 0 | For example, in the phrase âCompany-A last week purchased rival Marshalls from Company-Bâ, the purchased company is Marshalls, not Company-B. |
Using less training data than other systems, their NER can perform as well as other state-of-the-art NERs. | 0 | If is one of Monday, Tuesday, . . . |
They have made use of local and global features to deal with the instances of same token in a document. | 0 | Both BBN and NYU have tagged their own data to supplement the official training data. |
This paper talks about Unsupervised Models for Named Entity Classification. | 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. |
Here we present two algorithms. | 0 | Given around 90,000 unlabeled examples, the methods described in this paper classify names with over 91% accuracy. |
The bias of automatic methods in favour of statistical systems seems to be less pronounced on out-of-domain test data. | 0 | Figure 1 provides some statistics about this corpus. |
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 | First, a non-anaphoric NP classifier identifies definite noun phrases that are existential, using both syntactic rules and our learned existential NP recognizer (Bean and Riloff, 1999), and removes them from the resolution process. |
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 | For example, in TAG's a derived auxiliary tree spans two substrings (to the left and right of the foot node), and the adjunction operation inserts another substring (spanned by the subtree under the node where adjunction takes place) between them (see Figure 3). |
The TRIE model uses less memory than the smallest lossless alternative and is still faster than SRILM. | 0 | Therefore, performance is more closely tied to the underlying data structure than to the cache. |
However, using the top-level semantic classes of WordNet proved to be problematic as the class distinctions are too coarse. | 0 | (Kehler, 1997) also used a DempsterShafer model to merge evidence from different sources for template-level coreference. |
Most IE researchers have been creating paraphrase knowledge by hand and specific tasks. | 0 | Find keywords for each NE pair The keywords are found for each NE category pair. |
Human judges also pointed out difficulties with the evaluation of long sentences. | 0 | Most of these groups follow a phrase-based statistical approach to machine translation. |
This paper presents methods to query N-gram language models, minimizing time and space costs. | 0 | In this section, we extend state to optimize left-to-right queries. |
The problem of coreference resolution has received considerable attention, including theoretical discourse models and supervised machine learning systems. | 0 | We found that contextual role knowledge was more beneficial for pronouns than for definite noun phrases. |
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 | In Section 5, we try to compare results of MENE, IdentiFinder, and MENERGI. |
They focused on phrases which two Named Entities, and proceed in two stages. | 0 | In general, different modalities (âplanned to buyâ, âagreed to buyâ, âboughtâ) were considered to express the same relationship within an extraction setting. |
Here we present two algorithms. | 0 | It may be more realistic to replace the second criteria with a softer one, for example (Blum and Mitchell 98) suggest the alternative Alternatively, if Ii and 12 are probabilistic learners, it might make sense to encode the second constraint as one of minimizing some measure of the distance between the distributions given by the two learners. |
There are clustering approaches that assign a single POS tag to each word type. | 0 | We consider the unsupervised POS induction problem without the use of a tagging dictionary. |
The second algorithm builds on a boosting algorithm called AdaBoost. | 0 | The task can be considered to be one component of the MUC (MUC-6, 1995) named entity task (the other task is that of segmentation, i.e., pulling possible people, places and locations from text before sending them to the classifier). |
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 difference is due to more careful S-NOM NP NP NP VP VBG :: b NP restoring NP ADJP NN :: b NP NN NP NP ADJP DTJJ ADJP DTJJ NN :: b NP NP NP ADJP ADJP DTJJ J ..i NN :: b NP NP NP ADJP ADJP DTJJ NN _;� NP PRP DTJJ DTJJ J ..i _;� PRP J ..i NN _;� NP PRP DTJJ NN _;� NP PRP DTJJ J ..i role its constructive effective (b) Stanford (c) Berkeley (d) Bik el (a) Reference Figure 4: The constituent Restoring of its constructive and effective role parsed by the three different models (gold segmentation). |
The PROBING data structure uses linear probing hash tables and is designed for speed. | 0 | Adam Pauls provided a pre-release comparison to BerkeleyLM and an initial Java interface. |
The overall performance of their joint framework demonstrated that a probability distribution obtained over mere syntactic contexts using a Treebank grammar and a data-driven lexicon outperformed upper bounds proposed by previous joint disambiguation systems and achieved segmentation and parsing results on a par with state-of-the-art standalone applications results. | 0 | Co-occurrences among the particles themselves are subject to further syntactic and lexical constraints relative to the stem. |
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 | While it is essential to be fluent in the target language, it is not strictly necessary to know the source language, if a reference translation was given. |
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 | The function A : F —* C maps from the language specific fine-grained tagset F to the coarser universal tagset C and is described in detail in §6.2: Note that when tx(y) = 1 the feature value is 0 and has no effect on the model, while its value is −oc when tx(y) = 0 and constrains the HMM’s state space. |
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 | There, a lattice is used to represent the possible sentences resulting from an interpretation of an acoustic model. |
This paper talks about KenLM: Faster and Smaller Language Model Queries. | 0 | TPT Germann et al. (2009) describe tries with better locality properties, but did not release code. |
This paper discusses the Potsdam Commentary Corpus, a corpus of german assembeled by potsdam university. | 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 | The sources of our dictionaries are listed in Table 2. |
Each out-of-domain phrase pair was characterized by a set of simple features intended to reflect how useful it would be. | 0 | Intuitively, it places more weight on OUT when less evidence from IN is available. |
They focused on phrases which two Named Entities, and proceed in two stages. | 1 | We focus on phrases which connect two Named Entities (NEs), and proceed in two stages. |
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 | (a) 1 § . ;m t 7 leO z h e 4 pil m a 3 lu 4 sh an g4 bi ng 4 t h i s CL (assi fier) horse w ay on sic k A SP (ec t) 'This horse got sick on the way' (b) 1§: . til y zhe4 tiao2 ma3lu4 hen3 shao3 this CL road very few 'Very few cars pass by this road' :$ chel jinglguo4 car pass by 2. |
The second algorithm builds on a boosting algorithm called AdaBoost. | 0 | The NP is a complement to a preposition, which is the head of a PP. |
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 | Nonstochastic lexical-knowledge-based approaches have been much more numer ous. |
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 | However, 1 http://maxent.sourceforge.net 3.2 Testing. |
These clusters are computed using an SVD variant without relying on transitional structure. | 0 | 41. |
The PROBING data structure uses linear probing hash tables and is designed for speed. | 0 | Part of the gap between resident and virtual memory is due to the time at which data was collected. |
Koehn and Monz carried out an extensive manual and automatic evaluation of machine translation performance on European language pairs. | 0 | In-domain Systran scores on this metric are lower than all statistical systems, even the ones that have much worse human scores. |
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 | Note that these observa sider suffix features, capitalization features, punctuation, and digit features. |
Using less training data than other systems, their NER can perform as well as other state-of-the-art NERs. | 0 | Global context from the whole document is available and can be exploited in a natural manner with a maximum entropy classifier. |
they evaluate various specific aspects of the segmentation, as well as the overall segmentation performance. | 0 | As can be seen, GR and this "pared-down" statistical method perform quite similarly, though the statistical method is still slightly better.16 AG clearly performs much less like humans than these methods, whereas the full statistical algorithm, including morphological derivatives and names, performs most closely to humans among the automatic methods. |
Other kinds of productive word classes, such as company names, abbreviations,and place names can easily be handled given appropriate models. | 0 | In Chinese text, individual characters of the script, to which we shall refer by their traditional name of hanzi,Z are written one after another with no intervening spaces; a Chinese sentence is shown in Figure 1.3 Partly as a result of this, the notion "word" has never played a role in Chinese philological tradition, and the idea that Chinese lacks any thing analogous to words in European languages has been prevalent among Western sinologists; see DeFrancis (1984). |
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 | The correct resolution in sentence (c) depends on knowledge that kidnappers frequently blindfold their victims. |
This paper talks about KenLM: Faster and Smaller Language Model Queries. | 0 | It is generally considered to be fast (Pauls 29 − 1 probabilities and 2' − 2 non-zero backoffs. and Klein, 2011), with a default implementation based on hash tables within each trie node. |
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 | 6) are noisy, the results confirm that label propagation within the foreign language part of the graph adds significant quality for every language. |
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 | Taking the intersection of languages in these resources, and selecting languages with large amounts of parallel data, yields the following set of eight Indo-European languages: Danish, Dutch, German, Greek, Italian, Portuguese, Spanish and Swedish. |
The experimental tests are carried out on the Verbmobil task which is a limited-domain spoken-language task. | 0 | The sequence of states needed to carry out the word reordering example in Fig. |
The PROBING data structure uses linear probing hash tables and is designed for speed. | 0 | If there are too many distinct states, the decoder prunes low-scoring partial hypotheses, possibly leading to a search error. |
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 | Better grammars are shown here to improve performance on both morphological and syntactic tasks, providing support for the advantage of a joint framework over pipelined or factorized ones. |
The three parsers were trained and tuned by their creators on various sections of the WSJ portion of the Penn Treebank. | 0 | All four of the techniques studied result in parsing systems that perform better than any previously reported. |
The approach assumes that the word reordering is restricted to a few positions in the source sentence. | 0 | For à = 1, a new target language word is generated using the trigram language model p(eje0; e00). |
It also incorporates the Good-Turing methodin estimating the likelihoods of previously unseen constructions, including morphological derivatives and personal names. | 0 | 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. |
It also incorporates the Good-Turing methodin estimating the likelihoods of previously unseen constructions, including morphological derivatives and personal names. | 0 | However, they list two sets, one consisting of 28 fragments and the other of 22 fragments, in which they had 0% recall and precision. |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.