About: Improving Word Alignment Using Alignment of Deep Structures     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
Description
  • In this paper, we describe differences between a classical word alignment on the surface (word-layer alignment) and an alignment of deep syntactic sentence representations (tectogrammatical alignment). The deep structures we use are dependency trees containing content (autosemantic) words as their nodes. Most of other functional words, such as prepositions, articles, and auxiliary verbs are hidden. We introduce an algorithm which aligns such trees using perceptron-based scoring function. For evaluation purposes, a set of parallel sentences was manually aligned. We show that using statistical word alignment (GIZA ) can improve the tectogrammatical alignment. Surprisingly, we also show that the tectogrammatical alignment can be then used to significantly improve the original word alignment.
  • In this paper, we describe differences between a classical word alignment on the surface (word-layer alignment) and an alignment of deep syntactic sentence representations (tectogrammatical alignment). The deep structures we use are dependency trees containing content (autosemantic) words as their nodes. Most of other functional words, such as prepositions, articles, and auxiliary verbs are hidden. We introduce an algorithm which aligns such trees using perceptron-based scoring function. For evaluation purposes, a set of parallel sentences was manually aligned. We show that using statistical word alignment (GIZA ) can improve the tectogrammatical alignment. Surprisingly, we also show that the tectogrammatical alignment can be then used to significantly improve the original word alignment. (en)
Title
  • Improving Word Alignment Using Alignment of Deep Structures
  • Improving Word Alignment Using Alignment of Deep Structures (en)
skos:prefLabel
  • Improving Word Alignment Using Alignment of Deep Structures
  • Improving Word Alignment Using Alignment of Deep Structures (en)
skos:notation
  • RIV/00216208:11320/09:00206909!RIV10-AV0-11320___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1ET101120503)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 318861
http://linked.open...ai/riv/idVysledku
  • RIV/00216208:11320/09:00206909
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • Improving; Alignment; Using; Alignment; Structures (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [064156339BA7]
http://linked.open...v/mistoKonaniAkce
  • Berlin / Heidelberg
http://linked.open...i/riv/mistoVydani
  • Berlin / Heidelberg
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the 12th International Conference, TSD 2009
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Mareček, David
http://linked.open...vavai/riv/typAkce
http://linked.open...ain/vavai/riv/wos
  • 000270445700009
http://linked.open.../riv/zahajeniAkce
issn
  • 0302-9743
number of pages
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
http://localhost/t...ganizacniJednotka
  • 11320
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software