Morphological Tagging

18 papers with code • 0 benchmarks • 1 datasets

Morphological tagging is the task of assigning labels to a sequence of tokens that describe them morphologically. As compared to Part-of-speech tagging, morphological tagging also considers morphological features, such as case, gender or the tense of verbs.

Most implemented papers

Morphosyntactic Tagging with a Meta-BiLSTM Model over Context Sensitive Token Encodings

google/meta_tagger ACL 2018

In this paper, we investigate models that use recurrent neural networks with sentence-level context for initial character and word-based representations.

Multilingual Lexicalized Constituency Parsing with Word-Level Auxiliary Tasks

mcoavoux/mtg EACL 2017

We introduce a constituency parser based on a bi-LSTM encoder adapted from recent work (Cross and Huang, 2016b; Kiperwasser and Goldberg, 2016), which can incorporate a lower level character biLSTM (Ballesteros et al., 2015; Plank et al., 2016).

What do Neural Machine Translation Models Learn about Morphology?

boknilev/nmt-repr-analysis ACL 2017

Neural machine translation (MT) models obtain state-of-the-art performance while maintaining a simple, end-to-end architecture.

A General-Purpose Tagger with Convolutional Neural Networks

EggplantElf/sclem2017-tagger WS 2017

We present a general-purpose tagger based on convolutional neural networks (CNN), used for both composing word vectors and encoding context information.

Explaining Character-Aware Neural Networks for Word-Level Prediction: Do They Discover Linguistic Rules?

FredericGodin/ContextualDecomposition-NLP EMNLP 2018

In this paper, we investigate which character-level patterns neural networks learn and if those patterns coincide with manually-defined word segmentations and annotations.

Tree-Stack LSTM in Transition Based Dependency Parsing

kirnap/ku-dependency-parser2 CONLL 2018

We introduce tree-stack LSTM to model state of a transition based parser with recurrent neural networks.

Modeling Composite Labels for Neural Morphological Tagging

AleksTk/seq-morph-tagger CONLL 2018

Neural morphological tagging has been regarded as an extension to POS tagging task, treating each morphological tag as a monolithic label and ignoring its internal structure.

Multi Task Deep Morphological Analyzer: Context Aware Joint Morphological Tagging and Lemma Prediction

Saurav0074/morph_analyzer 21 Nov 2018

The ambiguities introduced by the recombination of morphemes constructing several possible inflections for a word makes the prediction of syntactic traits in Morphologically Rich Languages (MRLs) a notoriously complicated task.

Word Embeddings for the Armenian Language: Intrinsic and Extrinsic Evaluation

ispras-texterra/word-embeddings-eval-hy 7 Jun 2019

In this work, we intrinsically and extrinsically evaluate and compare existing word embedding models for the Armenian language.