# A Multi-task Approach for Named Entity Recognition in Social Media Data

arXiv: https://arxiv.org/abs/1906.04135 · HTML: https://mlsanity.com/paper/1906.04135/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Jun 2019.

## Built on by (most cited first, 18 of 18)

- [Are Multilingual Models Effective in Code-Switching?](https://mlsanity.com/paper/2103.13309/) (2021)
- [MultiCoNER: A Large-scale Multilingual dataset for Complex Named Entity Recognition](https://mlsanity.com/paper/2208.14536/) (2022)
- [Probing Pre-trained Auto-regressive Language Models for Named Entity Typing and Recognition](https://mlsanity.com/paper/2108.11857/) (2021)
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- [Scaling Creative Inspiration with Fine-Grained Functional Aspects of Ideas](https://mlsanity.com/paper/2102.09761/) (2021)
- [When Multi-Task Learning Meets Partial Supervision: A Computer Vision Review](https://mlsanity.com/paper/2307.14382/) (2023)
- [SoftNER: Mining Knowledge Graphs From Cloud Incidents](https://mlsanity.com/paper/2101.05961/) (2021)
- [Boosting Entity Mention Detection for Targetted Twitter Streams with Global Contextual Embeddings](https://mlsanity.com/paper/2201.11885/) (2022)
- [UM6P-CS at SemEval-2022 Task 11: Enhancing Multilingual and Code-Mixed Complex Named Entity Recognition via Pseudo Labels using Multilingual Transformer](https://mlsanity.com/paper/2204.13515/) (2022)
- [Multi-Granularity Cross-Modality Representation Learning for Named Entity Recognition on Social Media](https://mlsanity.com/paper/2210.14163/) (2022)
- [AsPOS: Assamese Part of Speech Tagger using Deep Learning Approach](https://mlsanity.com/paper/2212.07043/) (2022)
- [L3Cube-MahaSocialNER: A Social Media based Marathi NER Dataset and BERT models](https://mlsanity.com/paper/2401.00170/) (2023)
- [Part-of-Speech Tagger for Bodo Language using Deep Learning approach](https://mlsanity.com/paper/2401.03175/) (2024)
- [How Effective is Incongruity? Implications for Code-mix Sarcasm Detection](https://mlsanity.com/paper/2202.02702/) (2022)
- [LMN at SemEval-2022 Task 11: A Transformer-based System for English Named Entity Recognition](https://mlsanity.com/paper/2203.03546/) (2022)
- [Multi-features based Semantic Augmentation Networks for Named Entity Recognition in Threat Intelligence](https://mlsanity.com/paper/2207.00232/) (2022)
- [Extreme Multi-label Completion for Semantic Document Labelling with Taxonomy-Aware Parallel Learning](https://mlsanity.com/paper/2412.13809/) (2024)

## Abstract (arXiv)

Named Entity Recognition for social media data is challenging because of its inherent noisiness. In addition to improper grammatical structures, it contains spelling inconsistencies and numerous informal abbreviations. We propose a novel multi-task approach by employing a more general secondary task of Named Entity (NE) segmentation together with the primary task of fine-grained NE categorization. The multi-task neural network architecture learns higher order feature representations from word and character sequences along with basic Part-of-Speech tags and gazetteer information. This neural network acts as a feature extractor to feed a Conditional Random Fields classifier. We were able to obtain the first position in the 3rd Workshop on Noisy User-generated Text (WNUT-2017) with a 41.86% entity F1-score and a 40.24% surface F1-score.