Entity Retrieval
22 papers with code • 2 benchmarks • 4 datasets
Libraries
Use these libraries to find Entity Retrieval models and implementations
BEIR
ZESHEL
Most implemented papers
Evaluating Entity Disambiguation and the Role of Popularity in Retrieval-Based NLP
These experiments on AmbER sets show their utility as an evaluation tool and highlight the weaknesses of popular retrieval systems.
MuVER: Improving First-Stage Entity Retrieval with Multi-View Entity Representations
alibaba-nlp/muver
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EMNLP 2021
Entity retrieval, which aims at disambiguating mentions to canonical entities from massive KBs, is essential for many tasks in natural language processing.
EntQA: Entity Linking as Question Answering
wenzhengzhang/entqa
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ICLR 2022
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.
SGPT: GPT Sentence Embeddings for Semantic Search
muennighoff/sgpt
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To this end, we propose SGPT to use decoders for sentence embeddings and semantic search via prompting or fine-tuning.
TABi: Type-Aware Bi-Encoders for Open-Domain Entity Retrieval
hazyresearch/tabi
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Findings (ACL) 2022
Entity retrieval--retrieving information about entity mentions in a query--is a key step in open-domain tasks, such as question answering or fact checking.
Entity-aware Transformers for Entity Search
informagi/embert
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Pre-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. Recent research even claims that BERT is able to capture factual knowledge about entity relations and properties, the information that is commonly obtained from knowledge graphs.
R2D2: Robust Data-to-Text with Replacement Detection
Unfaithful text generation is a common problem for text generation systems.
No Parameter Left Behind: How Distillation and Model Size Affect Zero-Shot Retrieval
This has made distilled and dense models, due to latency constraints, the go-to choice for deployment in real-world retrieval applications.
OSLAT: Open Set Label Attention Transformer for Medical Entity Retrieval and Span Extraction
In this paper, we propose a method for linking an open set of entities that does not require any span annotations.
Modeling Fine-grained Information via Knowledge-aware Hierarchical Graph for Zero-shot Entity Retrieval
We extract the knowledge units from the corresponding context and then construct a mention/entity centralized graph.
