Morphological Analysis

58 papers with code • 0 benchmarks • 5 datasets

Morphological Analysis is a central task in language processing that can take a word as input and detect the various morphological entities in the word and provide a morphological representation of it.

Source: Towards Finite-State Morphology of Kurdish

Most implemented papers

Rotation-invariant convolutional neural networks for galaxy morphology prediction

benanne/kaggle-galaxies 24 Mar 2015

Unfortunately, even this approach does not scale well enough to keep up with the increasing availability of galaxy images.

Towards Deep Learning in Hindi NER: An approach to tackle the Labelled Data Scarcity

monikkinom/ner-lstm 31 Oct 2016

In this paper we describe an end to end Neural Model for Named Entity Recognition NER) which is based on Bi-Directional RNN-LSTM.

Morphological analysis using a sequence decoder

ai-ku/TrMor2018 TACL 2019

Our Morse implementation and the TrMor2018 dataset are available online to support future research\footnote{See \url{https://github. com/ai-ku/Morse. jl} for a Morse implementation in Julia/Knet \cite{knet2016mlsys} and \url{https://github. com/ai-ku/TrMor2018} for the new Turkish dataset.

An Unsupervised Method for Weighting Finite-state Morphological Analyzers

apertium/apertium-weighting-tools LREC 2020

In this paper, we have developed a method for weighting a morphological analyzer built using finite state transducers in order to disambiguate its results.

DEEMD: Drug Efficacy Estimation against SARS-CoV-2 based on cell Morphology with Deep multiple instance learning

sadegh-saberian/deemd 10 May 2021

DEEMD can be explored for use on other emerging viruses and datasets to rapidly identify candidate antiviral treatments in the future}.

Learning Symbolic Rules for Reasoning in Quasi-Natural Language

princeton-vl/metaqnl 23 Nov 2021

In this work, we ask how we can build a rule-based system that can reason with natural language input but without the manual construction of rules.

MBT: A Memory-Based Part of Speech Tagger-Generator

mikekestemont/anthem 11 Jul 1996

In this paper we show that a large-scale application of the memory-based approach is feasible: we obtain a tagging accuracy that is on a par with that of known statistical approaches, and with attractive space and time complexity properties when using {\em IGTree}, a tree-based formalism for indexing and searching huge case bases.}

Development of a Hindi Lemmatizer

sainimohit23/hindi-stemmer 24 May 2013

We live in a translingual society, in order to communicate with people from different parts of the world we need to have an expertise in their respective languages.