TweetTER: A Benchmark for Target Entity Retrieval on Twitter without Knowledge Bases (2024.lrec-main)
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| Challenge: | Entity linking is a well-established task in NLP consisting of associating entity mentions with entries in a knowledge base. |
| Approach: | They propose a benchmark that reframes entity linking as a binary entity retrieval task and uses a knowledge base to evaluate model performance. |
| Outcome: | The proposed benchmark aims to bridge the challenges in entity linking in noisy domains such as social media. |
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| Challenge: | Modern NLP systems are typically ill-equipped when applied to noisy user-generated text. |
| Approach: | They propose a new evaluation framework consisting of seven Twitter-specific classification tasks. |
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| Challenge: | Entity linking is a task that aims at associating an entity mention with a unique entity in a knowledge base. |
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Named Entity Recognition in Twitter: A Dataset and Analysis on Short-Term Temporal Shifts (2022.aacl-main)
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| Challenge: | Named Entity Recognition (NER) is a longstanding NLP task that consists of identifying an entity in a sentence or document. |
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Annotating the Tweebank Corpus on Named Entity Recognition and Building NLP Models for Social Media Analysis (2022.lrec-1)
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| Challenge: | Social media data such as Twitter messages pose a particular challenge to NLP systems because of their short, noisy nature. |
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Fine-Grained Evaluation for Entity Linking (D19-1)
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| Challenge: | Entity Linking (EL) is an Information Extraction task that identifies entity mentions in a text corpus and associates them with an unambiguous identifier in KBs such as Wikipedia, BabelNet, DBpedia, Wikidata and YAGO. |
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Entity Linking in 100 Languages (2020.emnlp-main)
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| Challenge: | Existing approaches to multilingual entity linking are cross-lingual, with a focus on zero-shot evaluation. |
| Approach: | They propose a new formulation for multilingual entity linking where language-specific mentions resolve to a language-agnostic Knowledge Base. |
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SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research (2023.findings-emnlp)
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Dimosthenis Antypas, Asahi Ushio, Francesco Barbieri, Leonardo Neves, Kiamehr Rezaee, Luis Espinosa-Anke, Jiaxin Pei, Jose Camacho-Collados
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| Challenge: | Entity linking systems often exploit relations between textual mentions to decide if the linking decisions are compatible. |
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TweetNLP: Cutting-Edge Natural Language Processing for Social Media (2022.emnlp-demos)
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Jose Camacho-collados, Kiamehr Rezaee, Talayeh Riahi, Asahi Ushio, Daniel Loureiro, Dimosthenis Antypas, Joanne Boisson, Luis Espinosa Anke, Fangyu Liu, Eugenio Martínez Cámara
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entity-linkings: A Unified Library for Entity Linking (2026.eacl-demo)
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| Challenge: | Entity linking (EL) is the task of mapping named entities in text to canonical entries in a knowledge base. |
| Approach: | They propose a unified library for using and developing entity linking systems . a strong emphasis is placed on usability, making it highly extensible . |
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