Semantic Parsing is the task of transducing natural language utterances into formal meaning representations. The target meaning representations can be defined according to a wide variety of formalisms. This include linguistically-motivated semantic representations that are designed to capture the meaning of any sentence such as λ-calculus or the abstract meaning representations. Alternatively, for more task-driven approaches to Semantic Parsing, it is common for meaning representations to represent executable programs such as SQL queries, robotic commands, smart phone instructions, and even general-purpose programming languages like Python and Java.
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The parameters of the auxiliary reward function are optimized with respect to the validation performance of a trained policy.
In this paper we describe question answering system for answering of complex questions over Wikidata knowledge base.
Point cloud is an important type of geometric data structure.
Ranked #2 on Scene Segmentation on ScanNet
Though designed for decaNLP, MQAN also achieves state of the art results on the WikiSQL semantic parsing task in the single-task setting.
Ranked #2 on Natural Language Inference on MultiNLI (Accuracy metric)
DOMAIN ADAPTATION MACHINE TRANSLATION NAMED ENTITY RECOGNITION NATURAL LANGUAGE INFERENCE QUESTION ANSWERING RELATION EXTRACTION SEMANTIC PARSING SEMANTIC ROLE LABELING SENTIMENT ANALYSIS TEXT CLASSIFICATION TRANSFER LEARNING
To learn a semantic parser from denotations, a learning algorithm must search over a combinatorially large space of logical forms for ones consistent with the annotated denotations.
Two important aspects of semantic parsing for question answering are the breadth of the knowledge source and the depth of logical compositionality.
We present SQLova, the first Natural-language-to-SQL (NL2SQL) model to achieve human performance in WikiSQL dataset.
Recent years have witnessed the burgeoning of pretrained language models (LMs) for text-based natural language (NL) understanding tasks.
Ranked #1 on Semantic Parsing on WikiTableQuestions