Matches in ScholarlyData for { ?s ?p ?o. }
- item-3 next item-4.
- item-3 previous item-2.
- item-4 type ListItem.
- item-4 hasContent vee-satayamas.
- item-4 next item-5.
- item-4 previous item-3.
- item-5 type ListItem.
- item-5 hasContent asanee-kawtrakul.
- item-5 previous item-4.
- 871 creator michael-rosner.
- 871 type InProceedings.
- 871 label "ODL: an Object Description Language for Lexical Information".
- 871 sameAs 871.
- 871 abstract "This paper describes ODL, a description language for lexical information that is being developed within the context of a national project called MLRS (Maltese Language Resource Server) whose goal is to create a national corpus and computational lexicon for the Maltese language. The main aim of ODL is to make the task of the lexicographer easier by allowing lexical specifications to be set out formally so that actual entries will conform to them. The paper describes some of the background motivation, the ODL language itself, and concludes with a short example of how lexical values expressed in ODL can be mapped to an existing tagset together with some speculations about future work.".
- 871 hasAuthorList authorList.
- 871 hasTopic Linguistics.
- 871 isPartOf proceedings.
- 871 keyword "LR Infrastructures and Architectures".
- 871 keyword "Lexicon, lexical database".
- 871 keyword "Tools, systems, applications".
- 871 title "ODL: an Object Description Language for Lexical Information".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasLastItem item-1.
- item-1 type ListItem.
- item-1 hasContent michael-rosner.
- 873 creator james-martin.
- 873 creator martha-palmer.
- 873 creator rodney-d-nielsen.
- 873 creator wayne-ward.
- 873 type InProceedings.
- 873 label "Annotating Students Understanding of Science Concepts".
- 873 sameAs 873.
- 873 abstract "This paper summarizes the annotation of fine-grained entailment relationships in the context of student answers to science assessment questions. We annotated a corpus of 15,357 answer pairs with 145,911 fine-grained entailment relationships. We provide the rationale for such fine-grained analysis and discuss its perceived benefits to an Intelligent Tutoring System. The corpus also has potential applications in other areas, such as question answering and multi-document summarization. Annotators achieved 86.2% inter-annotator agreement (Kappa=0.728, corresponding to substantial agreement) annotating the fine-grained facets of reference answers with regard to understanding expressed in student answers and labeling from one of five possible detailed relationship categories. The corpus described in this paper, which is the only one providing such detailed entailment annotations, is available as a public resource for the research community. The corpus is expected to enable application development, not only for intelligent tutoring systems, but also for general textual entailment applications, that is currently not practical.".
- 873 hasAuthorList authorList.
- 873 hasTopic Linguistics.
- 873 isPartOf proceedings.
- 873 keyword "Corpus (creation, annotation, etc.)".
- 873 keyword "Dialogue & Natural Interactivity".
- 873 keyword "Semantics".
- 873 title "Annotating Students Understanding of Science Concepts".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasItem item-3.
- authorList hasItem item-4.
- authorList hasLastItem item-4.
- item-1 type ListItem.
- item-1 hasContent rodney-d-nielsen.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent wayne-ward.
- item-2 next item-3.
- item-2 previous item-1.
- item-3 type ListItem.
- item-3 hasContent james-martin.
- item-3 next item-4.
- item-3 previous item-2.
- item-4 type ListItem.
- item-4 hasContent martha-palmer.
- item-4 previous item-3.
- 874 creator erin-fitzgerald.
- 874 creator frederick-jelinek.
- 874 type InProceedings.
- 874 label "Linguistic Resources for Reconstructing Spontaneous Speech Text".
- 874 sameAs 874.
- 874 abstract "The output of a speech recognition system is not always ideal for subsequent downstream processing, in part because speakers themselves often make mistakes. A system would accomplish speech reconstruction of its spontaneous speech input if its output were to represent, in flawless, fluent, and content-preserving English, the message that the speaker intended to convey. These cleaner speech transcripts would allow for more accurate language processing as needed for NLP tasks such as machine translation and conversation summarization, which often rely on grammatical input. Recognizing that supervised statistical methods to identify and transform ill-formed areas of the transcript will require richly labeled resources, we have built the Spontaneous Speech Reconstruction corpus. This small corpus of reconstructed and aligned conversational telephone speech transcriptions for the Fisher conversational telephone speech corpus (Strassel and Walker, 2004) was annotated on several levels including string transformations and predicate-argument structure, and will be shared with the linguistic research community.".
- 874 hasAuthorList authorList.
- 874 hasTopic Linguistics.
- 874 isPartOf proceedings.
- 874 keyword "Corpus (creation, annotation, etc.)".
- 874 keyword "Dialogue & Natural Interactivity".
- 874 keyword "Paraphrasing".
- 874 title "Linguistic Resources for Reconstructing Spontaneous Speech Text".
- authorList type List.
- authorList hasFirstItem item-1.
- authorList hasItem item-1.
- authorList hasItem item-2.
- authorList hasLastItem item-2.
- item-1 type ListItem.
- item-1 hasContent erin-fitzgerald.
- item-1 next item-2.
- item-2 type ListItem.
- item-2 hasContent frederick-jelinek.
- item-2 previous item-1.
- 875 creator hakimeh-fadaee.
- 875 creator mehrnoush-shamsfard.
- 875 type InProceedings.
- 875 label "A Hybrid Morphology-Based POS Tagger for Persian".
- 875 sameAs 875.
- 875 abstract "In many applications of natural language processing (NLP) grammatically tagged corpora are needed. Thus Part of Speech (POS) Tagging is of high importance in the domain of NLP. Many taggers are designed with different approaches to reach high performance and accuracy. These taggers usually deal with inter-word relations and they make use of lexicons. In this paper we present a new tagging algorithm with a hybrid approach. This algorithm combines the features of probabilistic and rule-based taggers to tag Persian unknown words. In contrast with many other tagging algorithms this algorithm deals with the internal structure of the words and it does not need any built in knowledge. The introduced tagging algorithm is domain independent because it uses morphological rules. In this algorithm POS tags are assigned to unknown word with a probability which shows the accuracy of the assigned POS tag. Although this tagger is proposed for Persian, it can be adapted to other languages by applying their morphological rules.".
- 875 hasAuthorList authorList.
- 875 hasTopic Linguistics.
- 875 isPartOf proceedings.
- 875 keyword "Acquisition, Machine Learning".
- 875 keyword "Morphology".
- 875 keyword "Tagging".
- 875 title "A Hybrid Morphology-Based POS Tagger for Persian".