Browse State-of-the-Art › Entity Retrieval
Entity Retrieval
28 papers with code · 0 benchmarks · 4 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
4 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
No subtask under this task in the archive's task tree.
Most implemented papers archive 2025-07-28
28 shown of 28 papers with code (56 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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17 Apr 2021 3 repositories listed Syntology ran 3 of 4 samples · 1 unverifiedTo address this, and to facilitate researchers to broadly evaluate the effectiveness of their models, we introduce Benchmarking-IR (BEIR), a robust and heterogeneous evaluation benchmark for information retrieval.
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10 Nov 2019 3 repositories listedThis paper introduces a conceptually simple, scalable, and highly effective BERT-based entity linking model, along with an extensive evaluation of its accuracy-speed trade-off.
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5 Oct 2021 2 repositories listed Syntology ran 9 of 9 samples · 0 unverified · 1 pointer-only (licence)A conventional approach to entity linking is to first find mentions in a given document and then infer their underlying entities in the knowledge base.
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2 Oct 2020 2 repositories listedFor instance, Encyclopedias such as Wikipedia are structured by entities (e.
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26 May 2025 1 repository listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)LogiCoL builds upon in-batch supervised contrastive learning, and learns dense retrievers to respect the subset and mutually-exclusive set relation between query results via two sets of soft constraints expressed via…
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18 Feb 2025 1 repository listedKnowledge base question answering (KBQA) aims to answer user questions in natural language using rich human knowledge stored in large KBs.
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9 Nov 2024 1 repository listedThis paper introduces annotative indexing, a novel framework that unifies and generalizes traditional inverted indexes, column stores, object stores, and graph databases.
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10 Oct 2024 1 repository listedLearned Sparse Retrieval (LSR) models use vocabularies from pre-trained transformers, which often split entities into nonsensical fragments.
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26 May 2024 1 repository listedNaive Retrieval-Augmented Generation (RAG) focuses on individual documents during retrieval and, as a result, falls short in handling networked documents which are very popular in many applications such as citation…
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19 Apr 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverifiedExtracting structured information from unstructured text is critical for many downstream NLP applications and is traditionally achieved by closed information extraction (cIE).
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21 Jun 2023 1 repository listedEntity Linking (EL) is a fundamental task for Information Extraction and Knowledge Graphs.
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30 Mar 2023 1 repository listedExisting conversational models are handled by a database(DB) and API based systems.
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20 Nov 2022 1 repository listedWe extract the knowledge units from the corresponding context and then construct a mention/entity centralized graph.
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12 Jul 2022 1 repository listedIn this paper, we propose a method for linking an open set of entities that does not require any span annotations.
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6 Jun 2022 1 repository listedThis has made distilled and dense models, due to latency constraints, the go-to choice for deployment in real-world retrieval applications.
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25 May 2022 1 repository listedUnfaithful text generation is a common problem for text generation systems.
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2 May 2022 1 repository listedPre-trained language models such as BERT have been a key ingredient to achieve state-of-the-art results on a variety of tasks in natural language processing and, more recently, also in information retrieval.
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18 Apr 2022 1 repository listedEntity retrieval--retrieving information about entity mentions in a query--is a key step in open-domain tasks, such as question answering or fact checking.
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17 Feb 2022 1 repository listed Syntology ran 1 of 1 samples · 0 unverifiedTo this end, we propose SGPT to use decoders for sentence embeddings and semantic search via prompting or fine-tuning.
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13 Sep 2021 1 repository listedEntity retrieval, which aims at disambiguating mentions to canonical entities from massive KBs, is essential for many tasks in natural language processing.
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12 Jun 2021 1 repository listedThese experiments on AmbER sets show their utility as an evaluation tool and highlight the weaknesses of popular retrieval systems.
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30 Apr 2021 1 repository listedThe first module is a state-of-the-art model for geolocation estimation of images.
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5 Nov 2020 1 repository listed Syntology ran 6 of 9 samples · 3 unverifiedWe propose a new formulation for multilingual entity linking, where language-specific mentions resolve to a language-agnostic Knowledge Base.
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6 May 2020 1 repository listedIn this research, we improve upon the current state of the art in entity retrieval by re-ranking the result list using graph embeddings.
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7 Sep 2017 1 repository listedA new approach to the study of Generalized Graphs as semantic data structures using machine learning techniques is presented.
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25 Jul 2017 1 repository listedWe discover how clusterings of experts correspond to committees in organizations, the ability of expert representations to encode the co-author graph, and the degree to which they encode academic rank.
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12 Jun 2017 1 repository listedUnsupervised learning of low-dimensional, semantic representations of words and entities has recently gained attention.
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15 Mar 2017 1 repository listedThis paper describes our approach for the triple scoring task at the WSDM Cup 2017.
Syntology lines on 6 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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