Memory-Based Semantic Parsing

نویسندگان

چکیده

Abstract We present a memory-based model for context- dependent semantic parsing. Previous approaches focus on enabling the decoder to copy or modify parse from previous utterance, assuming there is dependency between current and parses. In this work, we propose represent contextual information using an external memory. learn context memory controller that manages by maintaining cumulative meaning of sequential user utterances. evaluate our approach three parsing benchmarks. Experimental results show can better process context-dependent demonstrates improved performance without task-specific decoders.

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

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Symmetry-Based Semantic Parsing

Semantic parsing maps sentences to formal meaning representations, enabling question answering, natural language interfaces, and many other applications. However, there is no agreement on what the meaning representation should be, and constructing a sufficiently large corpus of sentence-meaning pairs for learning is extremely challenging. In this paper, we argue that both of these problems can ...

متن کامل

Memory-Based Shallow Parsing

We present memory-based learning approaches to shallow parsing and apply these to five tasks: base noun phrase identification, arbitrary base phrase recognition, clause detection, noun phrase parsing and full parsing. We use feature selection techniques and system combination methods for improving the performance of the memory-based learner. Our approach is evaluated on standard data sets and t...

متن کامل

Memory-Based Dependency Parsing

This paper reports the results of experiments using memory-based learning to guide a deterministic dependency parser for unrestricted natural language text. Using data from a small treebank of Swedish, memory-based classifiers for predicting the next action of the parser are constructed. The accuracy of a classifier as such is evaluated on held-out data derived from the treebank, and its perfor...

متن کامل

Semantic parsing based on FrameNet

This paper describes our method based on Support Vector Machines for automatically assigning semantic roles to constituents of English sentences. This method employs four different feature sets, one of which being first reported herein. The combination of features as well as the extended training data we considered have produced in the Senseval-3 experiments an F1-score of 92.5% for the unrestr...

متن کامل

Massively Parallel Memory-Based Parsing

This paper discusses a radically new scheme of natural language processing called massively parallel memory-based parsing. Most parsing schemes are rule-based or principle-based which involves extensive serial rule application. Thus, it is a time consuming task which requires a few seconds or even a few minutes to complete the parsing of one sentence. Also, the degree of par-allelism attained b...

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

ژورنال

عنوان ژورنال: Transactions of the Association for Computational Linguistics

سال: 2021

ISSN: ['2307-387X']

DOI: https://doi.org/10.1162/tacl_a_00422