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Found 13 papers, 0 papers with code
A Novel Machine Learning Based Approach for Post-OCR Error Detection
Post processing is the most conventional approach for correcting errors that are caused by Optical Character Recognition(OCR) systems.
A Data-Driven Semi-Automatic Framenet Development Methodology
FrameNet is a lexical semantic resource based on the linguistic theory of frame semantics.
A Deep Learning System for Automatic Extraction of Typological Linguistic Information from Descriptive Grammars
In this study, we present a deep learning system for the task of automatic extraction of linguistic features from textual descriptions of natural languages.
The LSCD Benchmark: a Testbed for Diachronic Word Meaning Tasks
The repository reflects the task's modularity by allowing model evaluation for WiC, WSI and LSCD.
The DURel Annotation Tool: Human and Computational Measurement of Semantic Proximity, Sense Clusters and Semantic Change
We present the DURel tool that implements the annotation of semantic proximity between uses of words into an online, open source interface.
From Linguistic Descriptions to Language Profiles
Language catalogues and typological databases are two important types of resources containing different types of knowledge about the world{'}s natural languages.
The DReaM Corpus: A Multilingual Annotated Corpus of Grammars for the World's Languages
There exist as many as 7000 natural languages in the world, and a huge number of documents describing those languages have been produced over the years.
Exploiting Frame-Semantics and Frame-Semantic Parsing for Automatic Extraction of Typological Information from Descriptive Grammars of Natural Languages
We describe a novel system for automatic extraction of typological linguistic information from descriptive grammars of natural languages, applying the theory of frame semantics in the form of frame-semantic parsing.
A Supervised Approach for Enriching the Relational Structure of Frame Semantics in FrameNet
Frame semantics is a theory of linguistic meanings, and is considered to be a useful framework for shallow semantic analysis of natural language.
An Open Source Persian Computational Grammar
Abstract In this paper, we describe a multilingual open-source computational grammar of Persian, developed in Grammatical Framework (GF) ― A type-theoretical grammar formalism.
