HDU: Cross-lingual Textual Entailment with SMT Features

نویسندگان

  • Katharina Wäschle
  • Sascha Fendrich
چکیده

We describe the Heidelberg University system for the Cross-lingual Textual Entailment task at SemEval-2012. The system relies on features extracted with statistical machine translation methods and tools, combining monolingual and cross-lingual word alignments as well as standard textual entailment distance and bag-of-words features in a statistical learning framework. We learn separate binary classifiers for each entailment direction and combine them to obtain four entailment relations. Our system yielded the best overall score for three out of four language pairs.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

FBK: Cross-Lingual Textual Entailment Without Translation

This paper overviews FBK’s participation in the Cross-Lingual Textual Entailment for Content Synchronization task organized within SemEval-2012. Our participation is characterized by using cross-lingual matching features extracted from lexical and semantic phrase tables and dependency relations. The features are used for multi-class and binary classification using SVMs. Using a combination of l...

متن کامل

Towards Cross-Lingual Textual Entailment

This paper investigates cross-lingual textual entailment as a semantic relation between two text portions in different languages, and proposes a prospective research direction. We argue that cross-lingual textual entailment (CLTE) can be a core technology for several cross-lingual NLP applications and tasks. Through preliminary experiments, we aim at proving the feasibility of the task, and pro...

متن کامل

ALTN: Word Alignment Features for Cross-lingual Textual Entailment

We present a supervised learning approach to cross-lingual textual entailment that explores statistical word alignment models to predict entailment relations between sentences written in different languages. Our approach is language independent, and was used to participate in the CLTE task (Task#8) organized within Semeval 2013 (Negri et al., 2013). The four runs submitted, one for each languag...

متن کامل

Detecting Semantic Equivalence and Information Disparity in Cross-lingual Documents

We address a core aspect of the multilingual content synchronization task: the identification of novel, more informative or semantically equivalent pieces of information in two documents about the same topic. This can be seen as an application-oriented variant of textual entailment recognition where: i) T and H are in different languages, and ii) entailment relations between T and H have to be ...

متن کامل

ECNUCS: Recognizing Cross-lingual Textual Entailment Using Multiple Text Similarity and Text Difference Measures

This paper presents our approach used for cross-lingual textual entailment task (task 8) organized within SemEval 2013. Crosslingual textual entailment (CLTE) tries to detect the entailment relationship between two text fragments in different languages. We solved this problem in three steps. Firstly, we use a off-the-shelf machine translation (MT) tool to convert the two input texts into the sa...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2012