Entity Linking System connecting NER and NED with DBpedia Lookup
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Updated
Dec 12, 2023 - Python
Entity resolution (also known as data matching, data linkage, record linkage, and many other terms) is the task of finding entities in a dataset that refer to the same entity across different data sources (e.g., data files, books, websites, and databases). Entity resolution is necessary when joining different data sets based on entities that may or may not share a common identifier (e.g., database key, URI, National identification number), which may be due to differences in record shape, storage location, or curator style or preference.
Entity Linking System connecting NER and NED with DBpedia Lookup
Undergraduate Final Project (needs README up to date!!) - Scientific paper soon to be included
Code of "A Read-and-Select Framework for Zero-shot Entity Linking" (EMNLP 2023 Findings).
Research and experiments on modern techniques of named entity recognition, entity linking and relation extraction on unstructured text containing not only English but also Russian language.
Collection of Python scripts to build a Solr index from selected Dutch and English DBpedia dumps.
Tool for Information extraction from Russian texts
Micro project on big data technologies via spark
Paper notes for Information Extraction, including Relation Extraction (RE), Named Entity Recognition (NER), Entity Linking (EL), Event Extraction (EE), Named Entity Disambiguation (NED).
DrNote is an open tagging tool for text annotation and entity linking based on OpenTapioca and WIkiData/Wikipedia. It provides an entity linking service with pre-trained data for medical annotations in multilingual settings. The processing of raw text as well as PDF by a tesseract backend is supported.
Industrial-strength Natural Language Processing (NLP) in Python
A Python package to generate document profiles and extract metadata from text in parallel using several Docker images and NLP tools/frameworks.
A bi-encoder model for named entity linking
This AI-powered tool extracts Subject-Predicate-Object (SPO) triplets from unstructured text using LLMs, performs entity standardization and relationship inference, and generates interactive, community-detected knowledge graphs with rich visualizations.
Entity search engines for Google and Wikidata. Helping to link the two together and provide a way to ground entities
Class generator for Spring Framework entities
MEDDOPROF: MEDical DOcuments PROFessions recognition shared task
MIC-CIS entry in PharmaCoNER, Bacteria Biotope (BB 2029) & SeeDev 2019 Shared Tasks in EMNLP '19
UMLS Medical Entity Linking. Adaptation of MedLinker (ECIR 2020) for the Social Domain.
Created by Halbert L. Dunn
Released 1946