Morphological Analysis
62 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.
Benchmarks
These leaderboards are used to track progress in Morphological Analysis
CELEX
Polyglot-NER
Latest papers
Hunspell for Sorani Kurdish Spell Checking and Morphological Analysis
Spell checking and morphological analysis are two fundamental tasks in text and natural language processing and are addressed in the early stages of the development of language technology.
Neural Morphology Dataset and Models for Multiple Languages, from the Large to the Endangered
We train neural models for morphological analysis, generation and lemmatization for morphologically rich languages.
DEEMD: Drug Efficacy Estimation against SARS-CoV-2 based on cell Morphology with Deep multiple instance learning
Sadegh-Saberian/MIL-COVID19-RxRx19a
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DEEMD can be explored for use on other emerging viruses and datasets to rapidly identify candidate antiviral treatments in the future}.
User-Generated Text Corpus for Evaluating Japanese Morphological Analysis and Lexical Normalization
Morphological analysis (MA) and lexical normalization (LN) are both important tasks for Japanese user-generated text (UGT).
The Role of Interpretable Patterns in Deep Learning for Morphology
By training the models on the same source but different target, we can compare what subwords are important for different tasks and how they relate to each other.
Neural Compound-Word (Sandhi) Generation and Splitting in Sanskrit Language
This paper describes neural network based approaches to the process of the formation and splitting of word-compounding, respectively known as the Sandhi and Vichchhed, in Sanskrit language.
Learning to Recombine and Resample Data for Compositional Generalization
Flexible neural sequence models outperform grammar- and automaton-based counterparts on a variety of tasks.
AraDIC: Arabic Document Classification using Image-Based Character Embeddings and Class-Balanced Loss
mahmouddaif/AraDIC
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ACL 2020
Classical and some deep learning techniques for Arabic text classification often depend on complex morphological analysis, word segmentation, and hand-crafted feature engineering.
Building a Hebrew Semantic Role Labeling Lexical Resource from Parallel Movie Subtitles
We present a semantic role labeling resource for Hebrew built semi-automatically through annotation projection from English.
CAMeL Tools: An Open Source Python Toolkit for Arabic Natural Language Processing
CAMeL-Lab/camel_tools
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LREC 2020
We present CAMeL Tools, a collection of open-source tools for Arabic natural language processing in Python.
