Matches in ScholarlyData for { ?s ?p ?o. }
- 25 abstract "The paper describes the treatment of some specific syntactic constructions in two treebanks of Latin according to a common set of annotation guidelines. Both projects work within the theoretical framework of Dependency Grammar, which has been demonstrated to be an especially appropriate framework for the representation of languages with a moderately free word order, where the linear order of constituents is broken up with elements of other constituents. The two projects are the first of their kind for Latin, so no prior established guidelines for syntactic annotation are available to rely on. The general model for the adopted style of representation is that used by the Prague Dependency Treebank, with departures arising from the Latin grammar of Pinkster, specifically in the traditional grammatical categories of the ablative absolute, the accusative + infinitive, and gerunds/gerundives. Sharing common annotation guidelines allows us to compare the datasets of the two treebanks for tasks such as mutually checking annotation consistency, diachronically studying specific syntactic constructions, and training statistical dependency parsers.".
- 25 hasAuthorList authorList.
- 25 hasTopic Linguistics.
- 25 isPartOf proceedings.
- 25 keyword "Corpus (creation, annotation, etc.)".
- 25 keyword "Digital libraries".
- 25 keyword "Syntax".
- 25 title "The Annotation Guidelines of the Latin Dependency Treebank and Index Thomisticus Treebank: the Treatment of some specific Syntactic Constructions in Latin".
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- item-1 hasContent david-bamman.
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- item-2 hasContent marco-passarotti.
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- item-3 hasContent roberto-busa.
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- item-4 type ListItem.
- item-4 hasContent gregory-crane.
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- 250 creator diamantino-caseiro.
- 250 creator joana-paulo-pardal.
- 250 creator joao-graca.
- 250 creator luisa-coheur.
- 250 type InProceedings.
- 250 label "Building a Golden Collection of Parallel Multi-Language Word Alignment".
- 250 sameAs 250.
- 250 abstract "This paper reports an experience on producing manual word alignments over six different language pairs (all combinations between Portuguese, English, French and Spanish) (Graça et al., 2008). Word alignment of each language pair is made over the first 100 sentences of the common test set from the Europarl corpora (Koehn, 2005), corresponding to 600 new annotated sentences. This collection is publicly available at http://www.l2f.inesc- id.pt/resources/translation/. It contains, to our knowledge, the first word alignment gold set for the Portuguese language, with three other languages. Besides, it is to our knowledge, the first multi-language manual word aligned parallel corpus, where the same sentences are annotated for each language pair. We started by using the guidelines presented at (Mariño, 2005) and performed several refinements: some due to under-specifications on the original guidelines, others because of disagreement on some choices. This lead to the development of an extensive new set of guidelines for multi-lingual word alignment annotation that, we believe, makes the alignment process less ambiguous. We evaluate the inter-annotator agreement obtaining an average of 91.6% agreement between the different language pairs.".
- 250 hasAuthorList authorList.
- 250 hasTopic Linguistics.
- 250 isPartOf proceedings.
- 250 keyword "Corpus (creation, annotation, etc.)".
- 250 keyword "Machine Translation, SpeechToSpeech Translation".
- 250 keyword "Statistical methods".
- 250 title "Building a Golden Collection of Parallel Multi-Language Word Alignment".
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- item-1 hasContent joao-graca.
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- item-2 hasContent joana-paulo-pardal.
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- item-3 hasContent luisa-coheur.
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- item-4 type ListItem.
- item-4 hasContent diamantino-caseiro.
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- 253 creator steliana-ivanova.
- 253 type InProceedings.
- 253 label "POS Tagging for German: how important is the Right Context?".
- 253 sameAs 253.
- 253 abstract "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 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%.".
- 253 hasAuthorList authorList.
- 253 hasTopic Linguistics.
- 253 isPartOf proceedings.
- 253 keyword "Acquisition, Machine Learning".
- 253 keyword "Tagging".
- 253 title "POS Tagging for German: how important is the Right Context?".
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- item-1 hasContent steliana-ivanova.
- 254 creator hugo-van-hamme.
- 254 creator jacques-duchateau.
- 254 creator leen-cleuren.
- 254 creator pol-ghesquiere.
- 254 type InProceedings.
- 254 label "Children s Oral Reading Corpus (CHOREC): Description and Assessment of Annotator Agreement".
- 254 sameAs 254.
- 254 abstract "Within the scope of the SPACE project, the CHildren s Oral REading Corpus (CHOREC) is developed. This database contains recorded, transcribed and annotated read speech (42 GB or 130 hours) of 400 Dutch speaking elementary school children with or without reading difficulties. Analyses of inter- and intra-annotator agreement are carried out in order to investigate the consistency with which reading errors are detected, orthographic and phonetic transcriptions are made, and reading errors and reading strategies are labeled. Percentage agreement scores and kappa values both show that agreement between annotations, and therefore the quality of the annotations, is high. Taken all double or triple annotations (for 10% resp. 30% of the corpus) together, % agreement varies between 86.4% and 98.6%, whereas kappa varies between 0.72 and 0.97 depending on the annotation tier that is being assessed. School type and reading type seem to account for systematic differences in % agreement, but these differences disappear when kappa values are calculated that correct for chance agreement. To conclude, an analysis of the annotation differences with respect to the *s label (i.e. a label that is used to annotate undistinguishable spelling behaviour), phoneme labels, reading strategy and error labels is given.".
- 254 hasAuthorList authorList.
- 254 hasTopic Linguistics.
- 254 isPartOf proceedings.
- 254 keyword "Corpus (creation, annotation, etc.)".
- 254 keyword "Other".
- 254 keyword "Speech resource/database".
- 254 title "Children s Oral Reading Corpus (CHOREC): Description and Assessment of Annotator Agreement".
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