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Crowdsourced Corpus with Entity Salience Annotations

2016-05-01 · LREC 2016 5 · Milan Dojchinovski, Dinesh Reddy, Tom{\'a}{\v{s}} Kliegr, Tom{\'a}{\v{s}} Vitvar, Harald Sack

In this paper, we present a crowdsourced dataset which adds entity salience (importance) annotations to the Reuters-128 dataset, which is subset of Reuters-21578. The dataset is distributed under a free license and publish in the NLP Interchange Format, which fosters interoperability and re-use. We show the potential of the dataset on the task of learning an entity salience classifier and report on the results from several experiments.

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WN-Salience: A Corpus of News Articles with Entity Salience Annotations

2020-05-01 · LREC 2020 5 · Chuan Wu, Evangelos Kanoulas, Maarten de Rijke, Wei Lu

Entities can be found in various text genres, ranging from tweets and web pages to user queries submitted to web search engines. Existing research either considers all entities in the text equally important, or heuristic…

Articles Entity Linking

OpenPI2.0: An Improved Dataset for Entity Tracking in Texts

2023-05-24 · Li Zhang, Hainiu Xu, Abhinav Kommula, Chris Callison-Burch 외

Much text describes a changing world (e.g., procedures, stories, newswires), and understanding them requires tracking how entities change. An earlier dataset, OpenPI, provided crowdsourced annotations of entity state cha…

Question Answering

GUMsley: Evaluating Entity Salience in Summarization for 12 English Genres

2024-01-31 · Jessica Lin, Amir Zeldes

As NLP models become increasingly capable of understanding documents in terms of coherent entities rather than strings, obtaining the most salient entities for each document is not only an important end task in itself bu…

Abstractive Text Summarization coreference-resolution Coreference Resolution Hallucination+2

Towards Better Text Understanding and Retrieval through Kernel Entity Salience Modeling

2018-05-03 · Chenyan Xiong, Zhengzhong Liu, Jamie Callan, Tie-Yan Liu

This paper presents a Kernel Entity Salience Model (KESM) that improves text understanding and retrieval by better estimating entity salience (importance) in documents. KESM represents entities by knowledge enriched dist…

Retrieval

Crowdsourcing Learning as Domain Adaptation: A Case Study on Named Entity Recognition

2021-05-31 · ACL 2021 5 · Xin Zhang, Guangwei Xu, Yueheng Sun, Meishan Zhang 외

Crowdsourcing is regarded as one prospective solution for effective supervised learning, aiming to build large-scale annotated training data by crowd workers. Previous studies focus on reducing the influences from the no…

Domain Adaptation named-entity-recognition Named Entity Recognition Named Entity Recognition (NER)+2