Evaluate Python libraries and open API standards

[Mandalka]

For scoring by named entity recognition class use Spacy, which is integrated with Open Semantic ETL.
For scoring by "more like this" and different scoring by fields like name or description use Solr/Elasticsearch index / API

For other scoring methods in issues evaluate existing Python libraries.

For API standards/parameters inspiration from similar Open Source software:

• NERD named entity recognition and disambiguation: http://nerd.eurecom.fr
• Open Refine Reconciliation Service API: https://github.com/OpenRefine/OpenRefine/wiki/Reconciliation-Service-API
• Nordlys: https://github.com/iai-group/nordlys
• Spacy: Named Entity Recognition API by spacy-services: https://github.com/explosion/spacy-services
• Europeana Entity API: https://pro.europeana.eu/resources/apis/entity#suggest
• Neonion Semantic Annotations recommends entities by wikidata: https://github.com/FUB-HCC/neonion
• Apache Stanbol disambiguation by Solr "more like this": https://stanbol.apache.org/docs/trunk/components/enhancer/engines/list.html

[Mandalka]

For results structure and output of REST-API using (extended) Open Refine Reconciliation Service API specification / format, so Open Entity Search API and Open Semantic ETL can be used by many other existing Software like Open Refine or other Open Refine Reconciliation Service clients and servers (f.e. available for Wikidata), too.