paper-with-me

Papers

Cross-Lingual Transfer for Distantly Supervised and Low-resources Indonesian NER

2019-07-25 · Fariz Ikhwantri

Manually annotated corpora for low-resource languages are usually small in quantity (gold), or large but distantly supervised (silver). Inspired by recent progress of injecting pre-trained language model (LM) on many Natural Language Processing (NLP) task, we proposed to fine-tune pre-trained language model from high-resources languages to low-resources languages to improve the performance of both scenarios. Our empirical experiment demonstrates significant improvement when fine-tuning pre-trained language model in cross-lingual transfer scenarios for small gold corpus and competitive results in large silver compare to supervised cross-lingual transfer, which will be useful when there is no parallel annotation in the same task to begin. We compare our proposed method of cross-lingual transfer using pre-trained LM to different sources of transfer such as mono-lingual LM and Part-of-Speech tagging (POS) in the downstream task of both large silver and small gold NER dataset by exploiting character-level input of bi-directional language model task.

📄 PDF Abstract BibTeX arXiv:1907.11158

Code (0)

등록된 구현이 없습니다.

Tasks

Cross-Lingual TransferLanguage ModelingLanguage ModellingNERPart-Of-Speech TaggingPOS

Similar Papers 제목 키워드 기반

Cross-Lingual Contrastive Learning for Fine-Grained Entity Typing for Low-Resource Languages

2022-05-01 · ACL 2022 5 · Xu Han, Yuqi Luo, Weize Chen, Zhiyuan Liu 외

Fine-grained entity typing (FGET) aims to classify named entity mentions into fine-grained entity types, which is meaningful for entity-related NLP tasks. For FGET, a key challenge is the low-resource problem — the compl…

Contrastive LearningEntity TypingMachine Translation

Combining Distantly Supervised Models with In Context Learning for Monolingual and Cross-Lingual Relation Extraction

2025-10-21 · Vipul Rathore, Malik Hammad Faisal, Parag Singla, Mausam arxiv

Distantly Supervised Relation Extraction (DSRE) remains a long-standing challenge in NLP, where models must learn from noisy bag-level annotations while making sentence-level predictions. While existing state-of-the-art …

Relation Extraction

Can Multilingual Language Models Transfer to an Unseen Dialect? A Case Study on North African Arabizi

2020-05-01 · Benjamin Muller, Benoit Sagot, Djamé Seddah

Building natural language processing systems for non standardized and low resource languages is a difficult challenge. The recent success of large-scale multilingual pretrained language models provides new modeling tools…

Dependency ParsingPart-Of-Speech TaggingTransliteration

PARE: A Simple and Strong Baseline for Monolingual and Multilingual Distantly Supervised Relation Extraction

2021-10-14 · ACL 2022 5 · Vipul Rathore, Kartikeya Badola, Mausam, Parag Singla

Neural models for distantly supervised relation extraction (DS-RE) encode each sentence in an entity-pair bag separately. These are then aggregated for bag-level relation prediction. Since, at encoding time, these approa…

RelationRelation ExtractionRelation PredictionSentence

PARE: A Simple and Strong Baseline for Monolingual and Multilingual Distantly Supervised Relation Extraction

2021-11-16 · ACL ARR November 2021 11 · Anonymous

Neural models for distantly supervised relation extraction (DS-RE) encode each sentence in an entity-pair bag separately. These are then aggregated for bag-level relation prediction. Since, at encoding time, these approa…

RelationRelation ExtractionRelation PredictionSentence