We describe our submission system to the SemEval-2016 Task 8 on Abstract Meaning Representation (AMR) Parsing. We attempt to improve AMR parsing by exploiting preposition semantic role labeling information retrieved from a multi-layer feed-forward neural network. Prepositional semantics is included as features into the transition-based AMR parsing system CAMR (Wang, Xue, and S. Pradhan 2015a). ...

This work is a study of the delimitation of complex prepositions (CP) as lexical units, items of a computational lexicon that includes compounds and phrases. In addition, given the utmost importance of spotting noun phrases (NP) in document retrieval systems, parsing prepositional structures such as “Prep1 N Prep2 X” prevents the fragment “N Prep2 X” from being detected as a noun phrase, i.e. t...

In the following research, types of interlingual phraseological equivalents, similes, and some metaphors in novels Turgenev Rudin A Nest Gentry are studied from perspective their structure, semantics, origin; attention is paid to differences related specifics realia lacunae translation (when reproduced Slovak English). We focus on biblical ancient phraseology, aphorisms, catchphrases, allusions...

The article looks into the problem of metaphor translation in framework narrative discourse. data for research was taken from a piece literary work ‘The Gulag Archipelago’ by A.I. Solzhenitsyn and its translations. translated narration does not only serve as source information about peculiarities writer’s culture but also promotes development enrichment receiving ethnical literature. In this co...

We present several unsupervised statistical models for the prepositional phrase attachment task that approach the accuracy of the best supervised methods for this task. Our unsupervised approach uses a heuristic based on attachment proximity and trains h'om raw text that is annotated with only part-oi;speech tags and morphologicM base forms, as opposed to attachment information. It is therefore...

This paper explores the task of building an accurate prepositional phrase attachment corpus for new genres while avoiding a large investment in terms of time and money by crowdsourcing judgments. We develop and present a system to extract prepositional phrases and their potential attachments from ungrammatical and informal sentences and pose the subsequent disambiguation tasks as multiple choic...

This project studies semi-supervised discovery of named entities, relational entities and prepositional phrase attachments within a read-the-web framework. Meanings of an entity can be improvised and updated faster in the internet world than printed references. The main idea of this project is to study the feasibility of characterizing entities by web content directly. The approach is that cont...

We have developed a method to resolve ambiguities in prepositional phrase (PP) attachment in German. We measure on the one hand the cooccurrence strength between nouns (N) and prepositions (P) and on the other hand between verbs (V) and prepositions. The competing values of N+P versus V+P are used to decide whether to attach a prepositional phrase to the noun or to the verb. We calculate the co...

Prepositional phrase attachment is a common source of ambiguity in natural language processing. We present an unsupervised corpus-based approach to prepositional phrase attachment that achieves similar performance to supervised methods. Unlike previous unsupervised approaches in which training data is obtained by heuristic extraction of unambiguous examples from a corpus, we use an iterative pr...

This paper investigates the use of machine learning algorithms to label modifier-noun compounds with a semantic relation. The attributes used as input to the learning algorithms are the web frequencies for phrases containing the modifier, noun, and a prepositional joining term. We compare and evaluate different algorithms and different joining phrases on Nastase and Szpakowicz’s (2003) dataset ...