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Japanese is often taken to be strictly head-final in its syntax. In our work on a broad-coverage, precision implemented HPSG for Japanese, we have found that while this is generally true, there are nonetheless a few minor exceptions to the broad trend. In this paper, we describe the grammar engineering project, present the exceptions we have found, and conclude that this kind of phenomenon motivates on the one hand the HPSG type hierarchical approach which allows for the statement of both broad generalizations and exceptions to those generalizations and on the other hand the usefulness of grammar engineering as a means of testing linguistic hypotheses.
Hybrid robust deep and shallow semantic processing for creativity support in document production
(2004)
The research performed in the DeepThought project (http://www.project-deepthought.net) aims at demonstrating the potential of deep linguistic processing if added to existing shallow methods that ensure robustness. Classical information retrieval is extended by high precision concept indexing and relation detection. We use this approach to demonstrate the feasibility of three ambitious applications, one of which is a tool for creativity support in document production and collective brainstorming. This application is described in detail in this paper. Common to all three applications, and the basis for their development is a platform for integrated linguistic processing. This platform is based on a generic software architecture that combines multiple NLP components and on robust minimal recursive semantics (RMRS) as a uniform representation language.
While the sortal constraints associated with Japanese numeral classifiers are wellstudied, less attention has been paid to the details of their syntax. We describe an analysis implemented within a broadcoverage HPSG that handles an intricate set of numeral classifier construction types and compositionally relates each to an appropriate semantic representation, using Minimal Recursion Semantics.
The research performed in the DeepThought project aims at demonstrating the potential of deep linguistic processing if combined with shallow methods for robustness. Classical information retrieval is extended by high precision concept indexing and relation detection. On the basis of this approach, the feasibility of three ambitious applications will be demonstrated, namely: precise information extraction for business intelligence; email response management for customer relationship management; creativity support for document production and collective brainstorming. Common to these applications, and the basis for their development is the XML-based, RMRS-enabled core architecture framework that will be described in detail in this paper. The framework is not limited to the applications envisaged in the DeepThought project, but can also be employed e.g. to generate and make use of XML standoff annotation of documents and linguistic corpora, and in general for a wide range of NLP-based applications and research purposes.
During the past fifty years sign languages have been recognised as genuine languages with their own syntax and distinctive phonology. In the case of sign languages, phonetic description characterises the manual and non-manual aspects of signing. The latter relate to facial expression and upper torso position. In the case of manual components these characterise hand shape, orientation and position, and hand/arm movement in three dimensional space around the signer's body. These phonetic charcaterisations can be notated as HamNoSys descriptions of signs which has an executable interpretation to drive an avatar.
The HPSG sign language generation component of a text to sign language system prototype is described. The assimilation of SL morphological features to generate signs which respect positional agreement in signing space are emphasised.
The Deep Linguistic Processing with HPSG Initiative (DELH-IN) provides the infrastructure needed to produce open-source semantic transfer-based machine translation systems. We have made available a prototype Japanese-English machine translation system built from existing resources include parsers, generators, bidirectional grammars and a transfer engine.
This paper proposes an annotating scheme that encodes honorifics (respectful words). Honorifics are used extensively in Japanese, reflecting the social relationship (e.g. social ranks and age) of the referents. This referential information is vital for resolving zero
pronouns and improving machine translation outputs. Annotating honorifics is a complex task that involves identifying a predicate with honorifics, assigning ranks to referents of the
predicate, calibrating the ranks, and connecting referents with their predicates.
We present a novel well-formedness condition for underspecified semantic representations which requires that every correct MRS representation must be a net. We argue that (almost) all correct MRS representations are indeed nets, and apply this condition to identify a set of eleven rules in the English Resource Grammar (ERG) with bugs in their semantics component. Thus we demonstrate that the net test is useful in grammar debugging.
The process of turning a hand-written HPSG theory into a working computational grammar requires complex considerations. Two leading platforms are available for implementing HPSG grammars: The LKB and TRALE. These platforms are based on different approaches, distinct in their underlying logics and implementation details. This paper adopts the perspective of a computational linguist whose goal is to implement an HPSG theory. It focuses on ten different dimensions, relevant to HPSG grammar implementation, and examines, compares, and evaluates the different means which the two approaches provide for implementing them. The paper concludes that the approaches occupy opposite positions on two axes: faithfulness to the hand-written theory and computational accessibility. The choice between them depends largely on the grammar writer's preferences regarding those properties.
This demo abstract describes the SmartWeb Ontology-based Information Extraction System (SOBIE). A key feature of SOBIE is that all information is extracted and stored with respect to the SmartWeb ontology. In this way, other components of the systems, which use the same ontology, can access this information in a straightforward way. We will show how information extracted by SOBIE is visualized within its original context, thus enhancing the browsing experience of the end user.
In this paper we describe SOBA, a sub-component of the SmartWeb multi-modal dialog system. SOBA is a component for ontologybased information extraction from soccer web pages for automatic population of a knowledge base that can be used for domainspecific question answering. SOBA realizes a tight connection between the ontology, knowledge base and the information extraction component. The originality of SOBA is in the fact that it extracts information from heterogeneous sources such as tabular structures, text and image captions in a semantically integrated way. In particular, it stores extracted information in a knowledge base, and in turn uses the knowledge base to interpret and link newly extracted information with respect to already existing entities.
We consider two alternatives for memory management in typed-feature-structure-based parsers by identifying structural properties of grammar signatures that may be of some predictive value in determining the consequences of those alternatives. We define these properties, summarize the results of a number of experiments on artificially constructed signatures with respect to the relative rank of their asymptotic cost at parse-time, and experimentally consider how they impact memory management.
In this paper, we report on a transformation scheme that turns a Categorial Grammar, more specifically, a Combinatory Categorial Grammar (CCG; see Baldridge, 2002) into a derivation- and meaning-preserving typed feature structure (TFS) grammar.
We describe the main idea which can be traced back at least to work by Karttunen (1986), Uszkoreit (1986), Bouma (1988), and Calder et al. (1988). We then show how a typed representation of complex categories can be extended by other constraints, such as modes, and indicate how the Lambda semantics of combinators is mapped into a TFS representation, using unification to perform perform alpha-conversion and beta-reduction (Barendregt, 1984). We also present first findings concerning runtime measurements, showing that the PET system, originally developed for the HPSG grammar framework, outperforms the OpenCCG parser by a factor of 8–10 in the time domain and a factor of 4–5 in the space domain.
In this paper I use the formal framework of minimalist grammars to implement a version of the traditional approach to ellipsis as 'deletion under syntactic (derivational) identity', which, in conjunction with canonical analyses of voice phenomena, immediately allows for voice mismatches in verb phrase ellipsis, but not in sluicing. This approach to ellipsis is naturally implemented in a parser by means of threading a state encoding a set of possible antecedent derivation contexts through the derivation tree. Similarities between ellipsis and pronominal resolution are easily stated in these terms. In the context of this implementation, two approaches to ellipsis in the transformational community are naturally seen as equivalent descriptions at different levels: the LF-copying approach to ellipsis resolution is best seen as a description of the parser, whereas the phonological deletion approach a description of the underlying relation between form and meaning.