Lexical Reference: a Semantic Matching Subtask
نویسندگان
چکیده
Semantic lexical matching is a prominent subtask within text understanding applications. Yet, it is rarely evaluated in a direct manner. This paper proposes a definition for lexical reference which captures the common goals of lexical matching. Based on this definition we created and analyzed a test dataset that was utilized to directly evaluate, compare and improve lexical matching models. We suggest that such decomposition of the global semantic matching task is critical in order to fully understand and improve individual components.
منابع مشابه
A Textual Entailment System using Web based Machine Translation System
The article presents the experiments carried out as part of the participation in Recognizing Inference in Text (NTCIR-9 RITE) @NTCIR9 for Japanese.NTCIR-9 RITE has four subtasks, Binary-class (BC) subtask, Multi-class (MC) subtask, Entrance Exam and NTCIR-9 RITE4QA. We have submitted a total of three unique runs (Run 1, Run 2 and Run 3) in the BC subtask and one run each in the MC Subtask, Entr...
متن کاملAn Unsupervised Model with Attention Autoencoders for Question Retrieval
Question retrieval is a crucial subtask for community question answering. Previous research focus on supervised models which depend heavily on training data and manual feature engineering. In this paper, we propose a novel unsupervised framework, namely reduced attentive matching network (RAMN), to compute semantic matching between two questions. Our RAMN integrates together the deep semantic r...
متن کاملDeveloping a Semantic Similarity Judgment Test for Persian Action Verbs and Non-action Nouns in Patients With Brain Injury and Determining its Content Validity
Objective: Brain trauma evidences suggest that the two grammatical categories of noun and verb are processed in different regions of the brain due to differences in the complexity of grammatical and semantic information processing. Studies have shown that the verbs belonging to different semantic categories lead to neural activity in different areas of the brain, and action verb processing is r...
متن کاملPreferred Lexical Access Route in Persian Learners of English: Associative, Semantic or Both
Background: Words in the Mental Lexicon (ML) construct semantic field through associative and/ or semantic connections, with a pervasive native speaker preference for the former. Non-native preferences, however, demand further inquiry. Previous studies have revealed inconsistent Lexical Access (LA) patterns due to the limitations in the methodology and response categorization. Objectives: To f...
متن کاملHLTC-HKUST: A Neural Network Paraphrase Classifier using Translation Metrics, Semantic Roles and Lexical Similarity Features
This paper describes the system developed by our team (HLTC-HKUST) for task 1 of SemEval 2015 workshop about paraphrase classification and semantic similarity in Twitter. We trained a neural network classifier over a range of features that includes translation metrics, lexical and syntactic similarity score and semantic features based on semantic roles. The neural network was trained taking int...
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 2006