The Effect of Syntactic Representation on Semantic Role Labeling
نویسندگان
چکیده
Almost all automatic semantic role labeling (SRL) systems rely on a preliminary parsing step that derives a syntactic structure from the sentence being analyzed. This makes the choice of syntactic representation an essential design decision. In this paper, we study the influence of syntactic representation on the performance of SRL systems. Specifically, we compare constituent-based and dependencybased representations for SRL of English in the FrameNet paradigm. Contrary to previous claims, our results demonstrate that the systems based on dependencies perform roughly as well as those based on constituents: For the argument classification task, dependencybased systems perform slightly higher on average, while the opposite holds for the argument identification task. This is remarkable because dependency parsers are still in their infancy while constituent parsing is more mature. Furthermore, the results show that dependency-based semantic role classifiers rely less on lexicalized features, which makes them more robust to domain changes and makes them learn more efficiently with respect to the amount of training data.
منابع مشابه
برچسبزنی خودکار نقشهای معنایی در جملات فارسی به کمک درختهای وابستگی
Automatic identification of words with semantic roles (such as Agent, Patient, Source, etc.) in sentences and attaching correct semantic roles to them, may lead to improvement in many natural language processing tasks including information extraction, question answering, text summarization and machine translation. Semantic role labeling systems usually take advantage of syntactic parsing and th...
متن کاملبرچسبزنی نقش معنایی جملات فارسی با رویکرد یادگیری مبتنی بر حافظه
Abstract Extracting semantic roles is one of the major steps in representing text meaning. It refers to finding the semantic relations between a predicate and syntactic constituents in a sentence. In this paper we present a semantic role labeling system for Persian, using memory-based learning model and standard features. Our proposed system implements a two-phase architecture to first identify...
متن کاملDependency-based Semantic Analysis of Natural-language Text
Semantic roles, logical relations such as AGENT or INSTRUMENT that hold between events and their participants and circumstances, need to be determined automatically by several types of applications in natural language processing. This process is referred to as semantic role labeling. This dissertation describes how to construct statistical models for semantic role labeling of English text, and ...
متن کاملA syntactic-semantic analysis of \"منصوب به نزع خافض\"based on the Holy Quran
One of important issues in the field of implication and aggression is "منصوب به نزع خافض". It is an idiom related to مفعول به "”. By referring to its definition, a syntactic-semantic analysis will be done in this paper. It tries to indicate what is the relationship between word and meaning and to what extent Arabic syntax focu...
متن کامل