Results 11 to 20 of about 379,251 (377)
FloraNER: A new dataset for species and morphological terms named entity recognition in French botanical text [PDF]
Data in BriefFloraNER is a distantly supervised named entity recognition dataset (NER). The dataset is built from botanical French literature extracted from the OCR-preprocessed flora of New Caledonia, provided by the National Museum of Natural History in France ...
Ayoub Nainia +5 more
doaj +2 more sources
Review on Named Entity Recognition [PDF]
Jisuanji kexue yu tansuo, 2022 In the field of natural language processing, named entity recognition is the first key step of information extraction. Named entity recognition task aims to recognize named entities from a large number of unstructured texts and classify them into ...
LI Dongmei, LUO Sisi, ZHANG Xiaoping, XU Fu
doaj +1 more source
Multilingual Fine-Grained Named Entity Recognition [PDF]
Computer Science Journal of Moldova, 2023 The “MultiCoNER II Multilingual Complex Named Entity Recognition” task\footnote[1]{\url{https://multiconer.github.io}} within SemEval 2023 competition focuses on identifying complex named entities (NEs), such as the titles of creative works (e.g., songs,
Viorica-Camelia Lupancu, Adrian Iftene
doaj +1 more source
On the Use of Parsing for Named Entity Recognition [PDF]
Applied Sciences, 2021 Parsing is a core natural language processing technique that can be used to obtain the structure underlying sentences in human languages. Named entity recognition (NER) is the task of identifying the entities that appear in a text. NER is a challenging natural language processing task that is essential to extract knowledge from texts in multiple ...
Miguel A. Alonso +2 more
openaire +4 more sources
GPT-NER: Named Entity Recognition via Large Language Models [PDF]
arXiv.org, 2023 Despite the fact that large-scale Language Models (LLM) have achieved SOTA performances on a variety of NLP tasks, its performance on NER is still significantly below supervised baselines.
Shuhe Wang +7 more
semanticscholar +1 more source
Few-NERD: A Few-shot Named Entity Recognition Dataset [PDF]
Annual Meeting of the Association for Computational Linguistics, 2021 Recently, considerable literature has grown up around the theme of few-shot named entity recognition (NER), but little published benchmark data specifically focused on the practical and challenging task. Current approaches collect existing supervised NER
Ning Ding +7 more
semanticscholar +1 more source
UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition [PDF]
International Conference on Learning Representations, 2023 Large language models (LLMs) have demonstrated remarkable generalizability, such as understanding arbitrary entities and relations. Instruction tuning has proven effective for distilling LLMs into more cost-efficient models such as Alpaca and Vicuna. Yet
Wenxuan Zhou +4 more
semanticscholar +1 more source
SemEval-2023 Task 2: Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2) [PDF]
International Workshop on Semantic Evaluation, 2023 We present the findings of SemEval-2023 Task 2 on Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2). Divided into 13 tracks, the task focused on methods to identify complex fine-grained named entities (like WRITTENWORK, VEHICLE ...
B. Fetahu +4 more
semanticscholar +1 more source
Survey of Chinese Named Entity Recognition [PDF]
Jisuanji kexue yu tansuo, 2022 The Chinese named entity recognition (NER) task is a sub-task within the information extraction domain, where the task goal is to find, identify and classify relevant entities, such as names of people, places and organizations, from sentences given a ...
ZHAO Shan, LUO Rui, CAI Zhiping
doaj +1 more source
Dynamic Named Entity Recognition
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023 8 pages, 6 figures, SAC ...
Tristan Luiggi +4 more
openaire +3 more sources