Part-Of-Speech Tagging
214 papers with code • 15 benchmarks • 26 datasets
Part-of-speech tagging (POS tagging) is the task of tagging a word in a text with its part of speech. A part of speech is a category of words with similar grammatical properties. Common English parts of speech are noun, verb, adjective, adverb, pronoun, preposition, conjunction, etc.
Example:
| Vinken | , | 61 | years | old |
|---|---|---|---|---|
| NNP | , | CD | NNS | JJ |
Benchmarks
These leaderboards are used to track progress in Part-Of-Speech Tagging
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Libraries
Use these libraries to find Part-Of-Speech Tagging models and implementationsDatasets
Penn Treebank
Universal Dependencies
CoNLL
CoNLL 2002
GUM
Latest papers
Sentence Embedding Models for Ancient Greek Using Multilingual Knowledge Distillation
In this work, we use a multilingual knowledge distillation approach to train BERT models to produce sentence embeddings for Ancient Greek text.
MC-DRE: Multi-Aspect Cross Integration for Drug Event/Entity Extraction
Extracting meaningful drug-related information chunks, such as adverse drug events (ADE), is crucial for preventing morbidity and saving many lives.
Enhancing Cross-lingual Transfer via Phonemic Transcription Integration
nhhoang96/phonemic_xlingual
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Particularly, we propose unsupervised alignment objectives to capture (1) local one-to-one alignment between the two different modalities, (2) alignment via multi-modality contexts to leverage information from additional modalities, and (3) alignment via multilingual contexts where additional bilingual dictionaries are incorporated.
Taqyim: Evaluating Arabic NLP Tasks Using ChatGPT Models
Large language models (LLMs) have demonstrated impressive performance on various downstream tasks without requiring fine-tuning, including ChatGPT, a chat-based model built on top of LLMs such as GPT-3. 5 and GPT-4.
Supplementary Features of BiLSTM for Enhanced Sequence Labeling
conglei2xu/global-context-mechanism
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Sequence labeling tasks require the computation of sentence representations for each word within a given sentence.
MasakhaPOS: Part-of-Speech Tagging for Typologically Diverse African Languages
masakhane-io/masakhane-pos
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In this paper, we present MasakhaPOS, the largest part-of-speech (POS) dataset for 20 typologically diverse African languages.
Technical Report: Impact of Position Bias on Language Models in Token Classification
mehdibenamorr/Token-Positional-Bias
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Therefore, we conduct an in-depth evaluation of the impact of position bias on the performance of LMs when fine-tuned on token classification benchmarks.
Does Manipulating Tokenization Aid Cross-Lingual Transfer? A Study on POS Tagging for Non-Standardized Languages
This can for instance be observed when finetuning PLMs on one language and evaluating them on data in a closely related language variety with no standardized orthography.
BRENT: Bidirectional Retrieval Enhanced Norwegian Transformer
ltgoslo/brent
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After training, we also separate the language model, which we call the reader, from the retriever components, and show that this can be fine-tuned on a range of downstream tasks.
Classification of US Supreme Court Cases using BERT-Based Techniques
shubham30vatsal/web-of-law
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We compare our results for two classification tasks: (1) a broad classification task with 15 categories and (2) a fine-grained classification task with 279 categories.
