1/5/2024 0 Comments Shoulders of Giants instal![]() ![]() ![]() The files used for this project can be divided into three categories. You will also need to manually download the files described in the next section. If you want to do anything more than simply running our API locally, you can skip the Docker steps and continue with installation from source. This section describes how to deploy REL on a local machine and setup the API. Result = process_results(mentions, predictions, input_text) Predictions, timing = model.predict(mentions) Model = EntityDisambiguation(base_url, wiki_version, config) Mentions, n_mentions = mention_detection.find_mentions(input_text, tagger_ngram) Tagger_ngram = Cmns(base_url, wiki_version, n=5) Mention_detection = MentionDetection(base_url, wiki_version) For ED, however, the spans field should consist of a list of tuples, where each tuple refers to the start position and length of a mention.įrom REL.mention_detection import MentionDetectionįrom REL.entity_disambiguation import EntityDisambiguation Users may access our API by using the example script below.įor EL, the spans field needs to be set to an empty list. Suggestions, improvements, and edits are most welcome. Entity Disambiguation (ED): Given a text and a list of mentions, the system assigns an entity (or NIL) to each mention.Entity linking (EL): Given a text, the system outputs a list of mention-entity pairs, where each mention is a n-gram from text and each entity is an entity in the knowledge base.REL utilizes English Wikipedia as a knowledge base and can be used for the following tasks: Additionally, in Dutch a 'rel' means a disturbance of the public order, which is exactly what we aim to achieve with the release of this package. REL has various meanings - one might first notice that it stands for relation, which is a suiting name for the problems that can be tackled with this package. REL is a modular Entity Linking package that is provided as a Python package as well as a web API. ![]()
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