Results 11 to 20 of about 328,579 (213)

Leveraging Concepts in Open Access Publications [PDF]

Journal of Data Mining and Digital Humanities, 2020
This paper addresses the integration of a Named Entity Recognition and Disambiguation (NERD) service within a group of open access (OA) publishing digital platforms and considers its potential impact on both research and scholarly publishing.
Andrea Bertino, Luca Foppiano, Laurent Romary, Pierre Mounier   +3 more
doaj   +5 more sources

Entity Disambiguation via Fusion Entity Decoding [PDF]

Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
Entity disambiguation (ED), which links the mentions of ambiguous entities to their referent entities in a knowledge base, serves as a core component in entity linking (EL). Existing generative approaches demonstrate improved accuracy compared to classification approaches under the standardized ZELDA benchmark.
Junxiong Wang, Ali Mousavi 0003, Omar Attia, Ronak Pradeep, Saloni Potdar, Alexander M. Rush, Umar Farooq Minhas, Yunyao Li 0001   +7 more
core   +5 more sources

Mention and Entity Description Co-Attention for Entity Disambiguation

Proceedings of the AAAI Conference on Artificial Intelligence, 2018
For the task of entity disambiguation, mention contexts and entity descriptions both contain various kinds of information content while only a subset of them are helpful for disambiguation. In this paper, we propose a type-aware co-attention model for entity disambiguation, which tries to identify the most discriminative words from ...
Feng Nie, Yunbo Cao, Jinpeng Wang 0001, Chin-Yew Lin, Rong Pan   +4 more
openaire   +3 more sources

Entity Disambiguation with Web Links [PDF]

Transactions of the Association for Computational Linguistics, 2021
Entity disambiguation with Wikipedia relies on structured information from redirect pages, article text, inter-article links, and categories. We explore whether web links can replace a curated encyclopaedia, obtaining entity prior, name, context, and coherence models from a corpus of web pages with links to Wikipedia.
Andrew Chisholm, Ben Hachey
doaj   +3 more sources

Learning Entity Representation for Named Entity Disambiguation

, 2015
In this paper we present a novel disambiguation model, based on neural networks. Most existing studies focus on designing effective man-made features and complicated similarity measures to obtain better disambiguation performance. Instead, our method learns distributed representation of entity to measure similarity without man-made features.
Rui Cai 0002, Houfeng Wang, Junhao Zhang
openaire   +3 more sources

Mining evidences for named entity disambiguation

Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, 2013
Named entity disambiguation is the task of disambiguating named entity mentions in natural language text and link them to their corresponding entries in a knowledge base such as Wikipedia. Such disambiguation can help enhance readability and add semantics to plain text.
Yang Li 0150, Chi Wang 0001, Fangqiu Han, Jiawei Han 0001, Dan Roth 0001, Xifeng Yan   +5 more
openaire   +3 more sources

Named entity recognition: challenges in document annotation, gazetteer construction and disambiguation [PDF]

, 2013
The ' information explosion' has generated unprecedented amount of published information that is still growing at an astonishing rate. As the amount of information grows, the problem of managing the information becomes challenging.
Zhang, Ziqi
core   +6 more sources

Entity Disambiguation with Entity Definitions

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023
Local models have recently attained astounding performances in Entity Disambiguation (ED), with generative and extractive formulations being the most promising research directions. However, previous works limited their studies to using, as the textual representation of each candidate, only its Wikipedia title.
Luigi Procopio, Simone Conia, Edoardo Barba, Roberto Navigli   +3 more
openaire   +2 more sources

ExtEnD: Extractive Entity Disambiguation

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
Local models for Entity Disambiguation (ED) have today become extremely powerful, in most part thanks to the advent of large pre-trained language models. However, despite their significant performance achievements, most of these approaches frame ED through classification formulations that have intrinsic limitations, both computationally and from a ...
Barba, Edoardo, Procopio, Luigi, Navigli, Roberto   +2 more
openaire   +2 more sources

Global Entity Disambiguation with BERT

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022
We propose a global entity disambiguation (ED) model based on BERT. To capture global contextual information for ED, our model treats not only words but also entities as input tokens, and solves the task by sequentially resolving mentions to their referent entities and using resolved entities as inputs at each step.
Ikuya Yamada, Koki Washio, Hiroyuki Shindo, Yuji Matsumoto 0001   +3 more
openaire   +3 more sources