Barbara Plank
University of Groningen, Alfa-informatica, Graduate Student
Research Interests:
Abstract NL Het doel van de computationele taalkunde is het maken van systemen die in staat zijn natuurlijke taal te begrijpen en te produceren, net zoals wij mensen dat doen. Het maken van dergelijke systemen is moeilijk, onder andere... more
Abstract NL Het doel van de computationele taalkunde is het maken van systemen die in staat zijn natuurlijke taal te begrijpen en te produceren, net zoals wij mensen dat doen. Het maken van dergelijke systemen is moeilijk, onder andere vanwege het probleem van de ambiguïteit van natuurlijke taal. In dit proefschrift ligt de focus op het automatisch ontleden, het bepalen van welke woorden en woordgroepen bij elkaar
Abstract. We evaluate two very different methods for domain adaptation of graph-based dependency parsers on the EVALITA 2011 Domain Adaptation data, namely instance-weighting [10] and self-training [9, 6]. Since the source and target... more
Abstract. We evaluate two very different methods for domain adaptation of graph-based dependency parsers on the EVALITA 2011 Domain Adaptation data, namely instance-weighting [10] and self-training [9, 6]. Since the source and target domains (newswire and law, respectively) were very similar, instance-weighting was unlikely to be efficient, but some of the semi-supervised approaches led to significant improvements on development data. Unfortunately, this improvement did not carry over to the released test data.
Abstract NL Het doel van de computationele taalkunde is het maken van systemen die in staat zijn natuurlijke taal te begrijpen en te produceren, net zoals wij mensen dat doen. Het maken van dergelijke systemen is moeilijk, onder andere... more
Abstract NL Het doel van de computationele taalkunde is het maken van systemen die in staat zijn natuurlijke taal te begrijpen en te produceren, net zoals wij mensen dat doen. Het maken van dergelijke systemen is moeilijk, onder andere vanwege het probleem van de ambiguïteit van natuurlijke taal. In dit proefschrift ligt de focus op het automatisch ontleden, het bepalen van welke woorden en woordgroepen bij elkaar
Abstract This paper evaluates two semi-supervised techniques for the adaptation of a parse selection model to Wikipedia domains. The techniques examined are Structural Correspondence Learning (SCL)(Blitzer et al., 2006) and Self-training... more
Abstract This paper evaluates two semi-supervised techniques for the adaptation of a parse selection model to Wikipedia domains. The techniques examined are Structural Correspondence Learning (SCL)(Blitzer et al., 2006) and Self-training (Abney, 2007; McClosky et al., 2006). A preliminary evaluation favors the use of SCL over the simpler self-training techniques.
Abstract This paper presents an on-going project aiming at enhancing the OPAC (Online Public Access Catalog) search system of the Library of the Free University of Bozen-Bolzano with multilingual access. The Multilingual search system... more
Abstract This paper presents an on-going project aiming at enhancing the OPAC (Online Public Access Catalog) search system of the Library of the Free University of Bozen-Bolzano with multilingual access. The Multilingual search system (MUSIL), we have developed, integrates advanced linguistic technologies in a user friendly interface and bridges the gap between the world of free text search and the world of conceptual librarian search.
Abstract An attractive property of attribute-value grammars is their reversibility. Attribute-value grammars are usually coupled with separate statistical components for parse selection and fluency ranking. We propose reversible... more
Abstract An attractive property of attribute-value grammars is their reversibility. Attribute-value grammars are usually coupled with separate statistical components for parse selection and fluency ranking. We propose reversible stochastic attribute-value grammars, in which a single statistical model is employed both for parse selection and fluency ranking.
ABSTRACT A major challenge for Natural Language Processing (NLP) is the inherent ambiguity of Natural Language. In parsing, a specific area of NLP, the ambiguity problem is characterized by multiple alternative syntactic analyses for a... more
ABSTRACT A major challenge for Natural Language Processing (NLP) is the inherent ambiguity of Natural Language. In parsing, a specific area of NLP, the ambiguity problem is characterized by multiple alternative syntactic analyses for a given sentence. In order to address the disambiguation problem, the present study tries to incorporate domain-awareness into the task of parsing. A treebank, as a collection of syntactically annotated sentences, might intuitively contain a set of concepts.
Abstract The 4th Workshop on “Semantic Processing of Legal Texts”(SPLeT–2012) presents the first multilingual shared task on Dependency Parsing of Legal Texts. In this paper, we define the general task and its internal organization into... more
Abstract The 4th Workshop on “Semantic Processing of Legal Texts”(SPLeT–2012) presents the first multilingual shared task on Dependency Parsing of Legal Texts. In this paper, we define the general task and its internal organization into sub–tasks, describe the datasets and the domain–specific linguistic peculiarities characterizing them. We finally report the results achieved by the participating systems, describe the underlying approaches and provide a first analysis of the final test results.
Abstract. Agile software development puts more emphasis on working programs than on documentation. However, this may cause complications from the management perspective when an overview of the progress achieved within a project needs to... more
Abstract. Agile software development puts more emphasis on working programs than on documentation. However, this may cause complications from the management perspective when an overview of the progress achieved within a project needs to be provided. In this paper, we outline the potential for applying natural language processing (NLP) in order to support agile development.