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Found 11 papers, 3 papers with code
Neural Architectures for Nested NER through Linearization
We propose two neural network architectures for nested named entity recognition (NER), a setting in which named entities may overlap and also be labeled with more than one label.
Ranked #3 on
Nested Mention Recognition
on ACE 2005
LemmaTag: Jointly Tagging and Lemmatizing for Morphologically-Rich Languages with BRNNs
We present LemmaTag, a featureless neural network architecture that jointly generates part-of-speech tags and lemmas for sentences by using bidirectional RNNs with character-level and word-level embeddings.
UDPipe at SIGMORPHON 2019: Contextualized Embeddings, Regularization with Morphological Categories, Corpora Merging
In the morphological analysis, our system placed tightly second: our morphological analysis accuracy was 93. 19, the winning system's 93. 23.
Evaluating Contextualized Embeddings on 54 Languages in POS Tagging, Lemmatization and Dependency Parsing
We present an extensive evaluation of three recently proposed methods for contextualized embeddings on 89 corpora in 54 languages of the Universal Dependencies 2. 3 in three tasks: POS tagging, lemmatization, and dependency parsing.
Ranked #1 on
Dependency Parsing
on Universal Dependencies
Czech Text Processing with Contextual Embeddings: POS Tagging, Lemmatization, Parsing and NER
We evaluate two meth ods for precomputing such embeddings, BERT and Flair, on four Czech text processing tasks: part-of-speech (POS) tagging, lemmatization, dependency pars ing and named entity recognition (NER).
The European Language Technology Landscape in 2020: Language-Centric and Human-Centric AI for Cross-Cultural Communication in Multilingual Europe
Multilingualism is a cultural cornerstone of Europe and firmly anchored in the European treaties including full language equality.
Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection
Universal Dependencies is an open community effort to create cross-linguistically consistent treebank annotation for many languages within a dependency-based lexicalist framework.
Prague Dependency Treebank -- Consolidated 1.0
We present a richly annotated and genre-diversified language resource, the Prague Dependency Treebank-Consolidated 1. 0 (PDT-C 1. 0), the purpose of which is - as it always been the case for the family of the Prague Dependency Treebanks - to serve both as a training data for various types of NLP tasks as well as for linguistically-oriented research.
Extending an Event-type Ontology: Adding Verbs and Classes Using Fine-tuned LLMs Suggestions
We have also carefully examined the correlation of the automatic scores with the human annotation.
Quality and Efficiency of Manual Annotation: Pre-annotation Bias
This paper presents an analysis of annotation using an automatic pre-annotation for a mid-level annotation complexity task -- dependency syntax annotation.
