Smatch: an Evaluation Metric for Semantic Feature Structures
نویسندگان
چکیده
The evaluation of whole-sentence semantic structures plays an important role in semantic parsing and large-scale semantic structure annotation. However, there is no widely-used metric to evaluate wholesentence semantic structures. In this paper, we present smatch, a metric that calculates the degree of overlap between two semantic feature structures. We give an efficient algorithm to compute the metric and show the results of an inter-annotator agreement study.
منابع مشابه
High-Fidelity Lexical Axiom Construction from Verb Glosses
This paper presents a rule-based approach to constructing lexical axioms from WordNet verb entries in an expressive semantic representation, Episodic Logic (EL). EL differs from other representations in being syntactically close to natural language and covering phenomena such as generalized quantification, modification, and intensionality while still allowing highly effective inference. The pre...
متن کاملEvaluation of the Parameters Involved in the Iris Recognition System
Biometric recognition is an automatic identification method which is based on unique features or characteristics possessed by human beings and Iris recognition has proved itself as one of the most reliable biometric methods available owing to the accuracy provided by its unique epigenetic patterns. The main steps in any iris recognition system are image acquisition, iris segmentation, iris norm...
متن کاملEnsemble Classification and Extended Feature Selection for Credit Card Fraud Detection
Due to the rise of technology, the possibility of fraud in different areas such as banking has been increased. Credit card fraud is a crucial problem in banking and its danger is over increasing. This paper proposes an advanced data mining method, considering both feature selection and decision cost for accuracy enhancement of credit card fraud detection. After selecting the best and most effec...
متن کاملL2F/INESC-ID at SemEval-2017 Tasks 1 and 2: Lexical and semantic features in word and textual similarity
This paper describes our approach to the SemEval-2017 “Semantic Textual Similarity” and “Multilingual Word Similarity” tasks. In the former, we test our approach in both English and Spanish, and use a linguistically-rich set of features. These move from lexical to semantic features. In particular, we try to take advantage of the recent Abstract Meaning Representation and SMATCH measure. Althoug...
متن کاملSemantic Feature Analysis Treatment for Anomia of Two Nonfluent Persian-Speaking Aphasic Patients
Objectives: Semantic Feature Analysis was designed to improve lexical retrieval of aphasic patients via activation of semantic networks of the words. In this approach, the anomic patients are cured with semantic information to assist oral naming. The purpose of this study was to examine the effects of Semantic Feature Analysis treatment on anomia of two nonfluent aphasic patients. Methods: A...
متن کاملذخیره 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 2013