Extern
Refine
Year of publication
Document Type
- Preprint (81) (remove)
Has Fulltext
- yes (81)
Is part of the Bibliography
- no (81)
Keywords
- Deutsch (16)
- Multicomponent Tree Adjoining Grammar (9)
- Syntaktische Analyse (8)
- Syntax (8)
- Semantik (6)
- Kongress (5)
- Optimalitätstheorie (5)
- Range Concatenation Grammar (5)
- Aufsatzsammlung (4)
- German (4)
Institute
- Extern (81)
LTAG semantics for questions
(2004)
This papers presents a compositional semantic analysis of interrogatives clauses in LTAG (Lexicalized Tree Adjoining Grammar) that captures the scopal properties of wh- and nonwh-quantificational elements. It is shown that the present approach derives the correct semantics for examples claimed to be problematic for LTAG semantic approaches based on the derivation tree. The paper further provides an LTAG semantics for embedded interrogatives.
This paper sets up a framework for LTAG (Lexicalized Tree Adjoining Grammar) semantics that brings together ideas from different recent approaches addressing some shortcomings of TAG semantics based on the derivation tree. Within this framework, several sample analyses are proposed, and it is shown that the framework allows to analyze data that have been claimed to be problematic for derivation tree based LTAG semantics approaches.
The problem of vocalization, or diacritization, is essential to many tasks in Arabic NLP. Arabic is generally written without the short vowels, which leads to one written form having several pronunciations with each pronunciation carrying its own meaning(s). In the experiments reported here, we define vocalization as a classification problem in which we decide for each character in the unvocalized word whether it is followed by a short vowel. We investigate the importance of different types of context. Our results show that the combination of using memory-based learning with only a word internal context leads to a word error rate of 6.64%. If a lexical context is added, the results deteriorate slowly.
In der folgenden Darstellung geht es einerseits darum, an Beispielen aufzuzeigen, inwiefern die schweizerdeutschen Mundarten und die deutsche Standardsprache in Lautung, Formenbildung, Satzbau und Wortschatz auseinandergehen können, andererseits aber immer auch um das Aufweisen von Gemeinsamkeiten. Oft werden nämlich bestimmte Erscheinungen des dialektalen Sprachbaus vorschnell als Eigenarten der Mundart verstanden, obwohl dieselben Erscheinungen auch im gesprochenen Hochdeutschen anzutreffen sind. Somit liegen also häufig nicht Unterschiede zwischen Mundart und Standardsprache vor, sondern Unterschiede zwischen gesprochener Sprache und geschriebener Sprache. [vollständige Überarbeitung für eine zweite Auflage]
This paper investigates the relation between TT-MCTAG, a formalism used in computational linguistics, and RCG. RCGs are known to describe exactly the class PTIME; simple RCG even have been shown to be equivalent to linear context-free rewriting systems, i.e., to be mildly context-sensitive. TT-MCTAG has been proposed to model free word order languages. In general, it is NP-complete. In this paper, we will put an additional limitation on the derivations licensed in TT-MCTAG. We show that TT-MCTAG with this additional limitation can be transformed into equivalent simple RCGs. This result is interesting for theoretical reasons (since it shows that TT-MCTAG in this limited form is mildly context-sensitive) and, furthermore, even for practical reasons: We use the proposed transformation from TT-MCTAG to RCG in an actual parser that we have implemented.
When a statistical parser is trained on one treebank, one usually tests it on another portion of the same treebank, partly due to the fact that a comparable annotation format is needed for testing. But the user of a parser may not be interested in parsing sentences from the same newspaper all over, or even wants syntactic annotations for a slightly different text type. Gildea (2001) for instance found that a parser trained on the WSJ portion of the Penn Treebank performs less well on the Brown corpus (the subset that is available in the PTB bracketing format) than a parser that has been trained only on the Brown corpus, although the latter one has only half as many sentences as the former. Additionally, a parser trained on both the WSJ and Brown corpora performs less well on the Brown corpus than on the WSJ one. This leads us to the following questions that we would like to address in this paper: - Is there a difference in usefulness of techniques that are used to improve parser performance between the same-corpus and the different-corpus case? - Are different types of parsers (rule-based and statistical) equally sensitive to corpus variation? To achieve this, we compared the quality of the parses of a hand-crafted constraint-based parser and a statistical PCFG-based parser that was trained on a treebank of German newspaper text.
Parsing coordinations
(2009)
The present paper is concerned with statistical parsing of constituent structures in German. The paper presents four experiments that aim at improving parsing performance of coordinate structure: 1) reranking the n-best parses of a PCFG parser, 2) enriching the input to a PCFG parser by gold scopes for any conjunct, 3) reranking the parser output for all possible scopes for conjuncts that are permissible with regard to clause structure. Experiment 4 reranks a combination of parses from experiments 1 and 3. The experiments presented show that n- best parsing combined with reranking improves results by a large margin. Providing the parser with different scope possibilities and reranking the resulting parses results in an increase in F-score from 69.76 for the baseline to 74.69. While the F-score is similar to the one of the first experiment (n-best parsing and reranking), the first experiment results in higher recall (75.48% vs. 73.69%) and the third one in higher precision (75.43% vs. 73.26%). Combining the two methods results in the best result with an F-score of 76.69.
The definition of similarity between sentences is formulated on the levels of words, POS tags, and chunks (Abney 91; Abney 96). The evaluation of this approach shows that while precision and recall based on the PARSEVAL measures (Black et al. 91) do not reach state of the art Parsers yet (F1=87.19 on syntactic constituents, F1=77.78 including functionargument structure), the parser shows a very reliable performance where function-argument structure is concerned (F1=96.52). The lower F-scores are very often due to unattached constituents.
In this paper, we will argue for a novel analysis of the auxiliary alternation in Early English, its development and subsequent loss which has broader consequences for the way that auxiliary selection is looked at cross-linguistically. We will present evidence that the choice of auxiliaries accompanying past participles in Early English differed in several significant respects from that in the familiar modern European languages. Specifically, while the construction with have became a full-fledged perfect by some time in the ME period, that with be was actually a stative resultative, which it remained until it was lost. We will show that this accounts for some otherwise surprising restrictions on the distribution of BE in Early English and allows a better understanding of the spread of HAVE through late ME and EModE. Perhaps more importantly, the Early English facts also provide insight into the genesis of the kind of auxiliary selection found in German, Dutch and Italian. Our analysis of them furthermore suggests a promising strategy for explaining cross-linguistic variation in auxiliary selection in terms of variation in the syntactico-semantic structure of the perfect. In this introductory section, we will first provide some background on the historical situation we will be discussing, then we will lay out the main claims for which we will be arguing in the paper.
Part-of-Speech tagging is generally performed by Markov models, based on bigram or trigram models. While Markov models have a strong concentration on the left context of a word, many languages require the inclusion of right context for correct disambiguation. We show for German that the best results are reached by a combination of left and right context. If only left context is available, then changing the direction of analysis and going from right to left improves the results. In a version of MBT (Daelemans et al., 1996) with default parameter settings, the inclusion of the right context improved POS tagging accuracy from 94.00% to 96.08%, thus corroborating our hypothesis. The version with optimized parameters reaches 96.73%.
Relative quantifier scope in German depends, in contrast to English, very much on word order. The scope possibilities of a quantifier are determined by its surface position, its base position and the type of the quantifier. In this paper we propose a multicomponent analysis for German quantifiers computing the scope of the quantifier, in particular its minimal nuclear scope, depending on the syntactic configuration it occurs in.
The purpose of this paper is to describe recent developments in the morphological, syntactic, and semantic annotation of the TüBa-D/Z treebank of German. The TüBa-D/Z annotation scheme is derived from the Verbmobil treebank of spoken German [4, 10], but has been extended along various dimensions to accommodate the characteristics of written texts. TüBa-D/Z uses as its data source the "die tageszeitung" (taz) newspaper corpus. The Verbmobil treebank annotation scheme distinguishes four levels of syntactic constituency: the lexical level, the phrasal level, the level of topological fields, and the clausal level. The primary ordering principle of a clause is the inventory of topological fields, which characterize the word order regularities among different clause types of German, and which are widely accepted among descriptive linguists of German [3, 6]. The TüBa-D/Z annotation relies on a context-free backbone (i.e. proper trees without crossing branches) of phrase structure combined with edge labels that specify the grammatical function of the phrase in question. The syntactic annotation scheme of the TüBa-D/Z is described in more detail in [12, 11]. TüBa-D/Z currently comprises approximately 15 000 sentences, with approximately 7 000 sentences being in the correction phase. The latter will be released along with an updated version of the existing treebank before the end of this year. The treebank is available in an XML format, in the NEGRA export format [1] and in the Penn treebank bracketing format. The XML format contains all types of information as described above, the NEGRA export format contains all sentenceinternal information while the Penn treebank format includes only those layers of information that can be expressed as pure tree structures. Over the course of the last year, more fine grained linguistic annotations have been added along the following dimensions: 1. the basic Stuttgart-Tübingen tagset, STTS, [9] labels have been enriched by relevant features of inflectional morphology, 2. named entity information has been encoded as part of the syntactic annotation, and 3. a set of anaphoric and coreference relations has been added to link referentially dependent noun phrases. In the following sections, we will describe each of these innovations in turn and will demonstrate how the additional annotations can be incorporated into one comprehensive annotation scheme.
This paper presents an LTAG analysis of reflexives like himself and reciprocals like each other. These items need to find a c-commanding antecedent from which they retrieve (part of) their own denotation and with which they syntactically agree. The relation between anaphoric item and antecendent must satisfy the following important locality conditions (Chomsky (1981)).
This paper argues for a particular architecture of OT syntax. This architecture hasthree core features: i) it is bidirectional, the usual production-oriented optimisation (called ‘first optimisation’ here) is accompanied by a second step that checks the recoverability of an underlying form; ii) this underlying form already contains a full-fledged syntactic specification; iii) especially the procedure checking for recoverability makes crucial use of semantic and pragmatic factors. The first section motivates the basic architecture. The second section shows with two examples, how contextual factors are integrated. The third section examines its implications for learning theory, and the fourth section concludes with a broader discussion of the advantages and disadvantages of the proposed model.
Das Chunkparsing bietet einen besonders vielversprechenden Ansatz zum robusten, partiellen Parsing mit dem Ziel einer breiten Datenabdeckung. Ziel beim Chunkparsing ist eine partielle, nicht-rekursive syntaktische Struktur. Dieser extrem effiziente Parsing-Ansatz läßt sich als Kaskade endlicher Transducer realisieren. In diesem Beitrag wird TüSBL vorgestellt, ein System, bei dem die Eingabe aus spontaner, gesprochener Spache besteht, die dem Parser in Form eines Worthypothesengraphen aus einem Spracherkenner zur Verfügung gestellt wird. Chunkparsing ist für eine solche Anwendung besonders geeignet, da es fragmentarische oder nicht wohlgeformte Äußerungen robust behandeln kann. Des weiteren wird eine Baumkonstruktionskomponente vorgestellt, die die partiellen Chunkstrukturen zu vollständigen Bäumen mit grammatischen Funktionen erweitert. Das System wird anhand manuell überprüfter Systemeingaben evaluiert, da sich die üblichen Evaluationsparameter hierfür nicht eignen.
Römische Bildnisse : Bibliographie, ungekürzt, mit den zu ergänzenden Literaturverweisen des Autors
(2010)
Originalfassung der in der Verlagspublikation um zahlreiche Literaturverweise gekürzten Bibliographie des Werkes: Götz Lahusen: Römische Bildnisse : Auftraggeber, Funktionen, Standorte. - Mainz : von Zabern, 2010. - Lizenz der WBG (Wiss. Buchges.) Darmstadt. - ISBN: 978-3-8053-3738-0. Pp. : EUR 49.90
This paper develops a framework for TAG (Tree Adjoining Grammar) semantics that brings together ideas from different recent approaches.Then, within this framework, an analysis of scope is proposed that accounts for the different scopal properties of quantifiers, adverbs, raising verbs and attitude verbs. Finally, including situation variables in the semantics, different situation binding possibilities are derived for different types of quantificational elements.
Existing analyses of German scrambling phenomena within TAG-related formalisms all use non-local variants of TAG. However, there are good reasons to prefer local grammars, in particular with respect to the use of the derivation structure for semantics. Therefore this paper proposes to use local TDGs, a TAG-variant generating tree descriptions that shows a local derivation structure. However the construction of minimal trees for the derived tree descriptions is not subject to any locality constraint. This provides just the amount of non-locality needed for an adequate analysis of scrambling. To illustrate this a local TDG for some German scrambling data is presented.
Recent approaches to Word Sense Disambiguation (WSD) generally fall into two classes: (1) information-intensive approaches and (2) information-poor approaches. Our hypothesis is that for memory-based learning (MBL), a reduced amount of data is more beneficial than the full range of features used in the past. Our experiments show that MBL combined with a restricted set of features and a feature selection method that minimizes the feature set leads to competitive results, outperforming all systems that participated in the SENSEVAL-3 competition on the Romanian data. Thus, with this specific method, a tightly controlled feature set improves the accuracy of the classifier, reaching 74.0% in the fine-grained and 78.7% in the coarse-grained evaluation.