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The first method builds on results from (Yarowsky 95) and (Blum and Mitchell 98).

For a description of the application of AdaBoost to various NLP problems see the paper by Abney, Schapire, and Singer in this volume.

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.

There is a guarantee of no crossing brackets but there is no guarantee that a constituent in the tree has the same children as it had in any of the three original parses.

Each out-of-domain phrase pair was characterized by a set of simple features intended to reflect how useful it would be.

This is motivated by taking β po(s|t) to be the parameters of a Dirichlet prior on phrase probabilities, then maximizing posterior estimates p(s|t) given the IN corpus.

This paper talks about Exploiting Diversity in Natural Language Processing: Combining Parsers.

The computation of Pfr1(c)1Mi M k (C)) has been sketched before in Equations 1 through 4.

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.

The operations must be linear and nonerasing, i.e., they can not duplicate or erase structure from their arguments.

It is annotated with several data: morphology, syntax, rhetorical structure, connectors, correference and informative structure.

Either save money at any cost - or give priority to education.

They proposed a single joint model for performing both morphological segmentation and syntactic disambiguation which bypasses the associated circularity.

Evaluation We use 8 different measures to evaluate the performance of our system on the joint disambiguation task.

Each out-of-domain phrase pair was characterized by a set of simple features intended to reflect how useful it would be.

The logistic function, whose outputs are in [0, 1], forces pp(s, t) <_ po(s, t).

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.

We showed in §2 that lexical ambiguity explains the underperformance of these categories.

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.

All three curves remain steep at the maximum training set size of 18818 trees.

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.

A secondary reference resolution classifier has information on the class assigned by the primary classifier.

Evaluation was done automatically using the BLEU score and manually on fluency and adequacy.

For more on the participating systems, please refer to the respective system description in the proceedings of the workshop.

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.

The input to AdaBoost is a set of training examples ((xi , yi), , (x„.„ yrn)).

There is no global pruning.

On average, 6 reference translations per automatic translation are available.

The experimental tests are carried out on the Verbmobil task which is a limited-domain spoken-language task.

Subsets of partial hypotheses with coverage sets C of increasing cardinality c are processed.

These clusters are computed using an SVD variant without relying on transitional structure.

9 50.2 +P RI OR be st me dia n 47.

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.

Our representation of contextual roles is based on information extraction patterns that are converted into simple caseframes.

The first method builds on results from (Yarowsky 95) and (Blum and Mitchell 98).

Our derivation is slightly different from the one presented in (Schapire and Singer 98) as we restrict at to be positive.

In this paper the authors present a stochastic finite-state model for segmenting Chinese text into words.

However, it is possible to personify any noun, so in children's stories or fables, i¥JJ1l.

The AdaBoost algorithm was developed for supervised learning.

We make the assumption that for each example, both xi,. and x2,2 alone are sufficient to determine the label yi.

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.

Mandarin exhibits several such processes, including A-not-A question formation, il­ lustrated in (3a), and adverbial reduplication, illustrated in (3b): 3.

Koehn and Monz carried out an extensive manual and automatic evaluation of machine translation performance on European language pairs.

The judgement of 4 in the first case will go to a vastly better system output than in the second case.

It is well-known that English constituency parsing models do not generalize to other languages and treebanks.

Table 9: Dev set results for sentences of length ≤ 70.

In order to realize the full potential of dependency-based syntactic parsing, it is desirable to allow non-projective dependency structures.

From the point of view of computational implementation this can be problematic, since the inclusion of non-projective structures makes the parsing problem more complex and therefore compromises efficiency and in practice also accuracy and robustness.

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.

We model po(s|t) using a MAP criterion over weighted phrase-pair counts: and from the similarity to (5), assuming y = 0, we see that wλ(s, t) can be interpreted as approximating pf(s, t)/po(s, t).

While many systems had similar performance, the results offered interesting insights, especially, about the relative performance of statistical and rule-based systems.

The judgements tend to be done more in form of a ranking of the different systems.

In this paper the authors present a stochastic finite-state model for segmenting Chinese text into words.

then define the best segmentation to be the cheapest or best path in Id(I) o D* (i.e., Id(I) composed with the transitive closure of 0).6 Consider the abstract example illustrated in Figure 2.

The model incorporates various recent techniques for incorporating and manipulating linguistic knowledge using finite-state transducers.

Their results are then compared with the results of an automatic segmenter.

This corpus has several advantages: it is annotated at different levels.

Reiche’s colleagues will make sure that the concept is waterproof.

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.

Coverage indicates the fraction of hypotheses in which the character yield exactly matched the reference.

An extended lexicon model is defined, and its likelihood is compared to a baseline lexicon model, which takes only single-word dependencies into account.

The approach recursively evaluates a quantity Q(C; j), where C is the set of already visited cities and sj is the last visited city.

However, using the top-level semantic classes of WordNet proved to be problematic as the class distinctions are too coarse.

During coreference resolution, the caseframe network provides evidence that an anaphor and prior noun phrase might be coreferent.

Evaluation was done automatically using the BLEU score and manually on fluency and adequacy.

Human judges also pointed out difficulties with the evaluation of long sentences.