Dangling entity detection
WebMar 9, 2024 · The dangling entity set is unavailable in most real-world scenarios, and manually mining the entity pairs that consist of entities with the same meaning is labor-consuming. In this paper, we... WebMar 11, 2024 · In the experimental part, we first show the superiority of SoTead on a commonly-used entity alignment dataset. Besides, to analyze the ability for dangling entity detection with other baselines, we construct a medical cross-lingual knowledge graph dataset, MedED, where our SoTead also reaches state-of-the-art performance. READ …
Dangling entity detection
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WebMar 9, 2024 · In this paper, we propose a novel accurate Unsupervised method for joint Entity alignment (EA) and Dangling entity detection (DED), called UED. The UED …
WebApr 7, 2024 · The dangling entity set is unavailable in most real-world scenarios, and manually mining the entity pairs that consist of entities with the same meaning is labor … WebJan 1, 2024 · After detecting and removing dangling entities, an incorporated entity alignment model in our framework can provide more robust alignment for remaining entities. Comprehensive experiments and analyses demonstrate the effectiveness of our framework.
WebDangling vulnerability Edit Edit source History Talk (0) Definition [] A dangling vulnerability is “ a set of properties about the internal environment for which there is no corresponding … WebDangling Entity Detection Several recent studies emphasize the problem of dangling entities in EA tasks.Zhao et al.(2024) andZeng et al.(2024) introduce threshold-based methods to identify dangling entities according to the distance between a source entity and its closest target entity. These two methods identify dangling
WebJun 28, 2024 · DBP2.0 DBP2.0 is a dataset for entity alignment with dangling cases, proposed by the ACL-2024 paper "Knowing the No-match: Entity Alignment with Dangling Cases". Browse Search Explore more content DBP2.0.zip(46.46 MB) File infoDownload file Fullscreen DBP2.0 CiteDownload(46.46 MB)ShareEmbed dataset
WebAbstract. This paper studies a new problem setting of entity alignment for knowledge graphs (KGs). Since KGs possess different sets of entities, there could be entities that cannot find alignment across them, leading to the problem of dangling entitiesdangling entities the phauxWebIn this way, we use the distribution as prole of the neighborhood of a source entity s, then we adopt a simple feed-forward neural network (FNN) bi- nary classier to determine whether s is dangling. The probability of s being a dangling entity can be calculated as p(y = 1 js) = sigmoid (FNN (d )). thephavongWebJun 4, 2024 · The framework can opt to abstain from predicting alignment for the detected dangling entities. We propose three techniques for dangling entity detection that are based on the distribution of... the phat italian killington vtWebMar 10, 2024 · Dangling Entity Detection Several recent studies emphasize the problem of dangling entities in EA tasks. Zhao et al. ( 2024) and Zeng et al. ( 2024) introduce threshold-based methods to identify dangling entities according to the distance between a source entity and its closest target entity. sick after eating carbsWebWe propose three techniques for dangling entity detection that are based on the distribution of nearest-neighbor distances, i.e., nearest neighbor classification, marginal ranking and background ranking. the ph at which most fungi thrive isWebJan 1, 2024 · We propose three techniques for dangling entity detection that are based on the distribution of nearest-neighbor distances, i.e., nearest neighbor classification, marginal ranking and background ... thephawxWebMar 11, 2024 · In the experimental part, we first show the superiority of SoTead on a commonly-used entity alignment dataset. Besides, to analyze the ability for dangling entity detection with other baselines, we construct a medical cross-lingual knowledge graph dataset, MedED, where our SoTead also reaches state-of-the-art performance. PDF … sick after eating bad food at a buffet