Elasticsearch
E699787
Elasticsearch is a distributed, RESTful search and analytics engine built on Apache Lucene, widely used for full-text search, log analytics, and real-time data exploration.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Elasticsearch canonical | 4 |
How this entity was disambiguated
This entity first appeared as the object of triple T7938614 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elasticsearch Context triple: [Katello, usesSearchEngine, Elasticsearch]
-
A.
Apache Solr
Apache Solr is an open-source enterprise search platform built on Apache Lucene, widely used for full-text search, faceted navigation, and real-time indexing of large-scale data.
-
B.
Apache Lucene
Apache Lucene is a high-performance, full-featured text search engine library written in Java and widely used as the core indexing and search technology in many applications and search platforms.
-
C.
Amazon OpenSearch Service
Amazon OpenSearch Service is a fully managed service from AWS for deploying, operating, and scaling OpenSearch and Elasticsearch-compatible search and analytics clusters in the cloud.
-
D.
Jetpack Search
Jetpack Search is a powerful WordPress search enhancement tool that provides fast, relevant, and customizable search results for websites using the Jetpack plugin.
-
E.
Laravel Scout
Laravel Scout is a Laravel package that provides a simple, driver-based full-text search abstraction for Eloquent models, integrating with services like Algolia and Meilisearch.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Elasticsearch Target entity description: Elasticsearch is a distributed, RESTful search and analytics engine built on Apache Lucene, widely used for full-text search, log analytics, and real-time data exploration.
-
A.
Apache Solr
Apache Solr is an open-source enterprise search platform built on Apache Lucene, widely used for full-text search, faceted navigation, and real-time indexing of large-scale data.
-
B.
Apache Lucene
Apache Lucene is a high-performance, full-featured text search engine library written in Java and widely used as the core indexing and search technology in many applications and search platforms.
-
C.
Amazon OpenSearch Service
Amazon OpenSearch Service is a fully managed service from AWS for deploying, operating, and scaling OpenSearch and Elasticsearch-compatible search and analytics clusters in the cloud.
-
D.
Jetpack Search
Jetpack Search is a powerful WordPress search enhancement tool that provides fast, relevant, and customizable search results for websites using the Jetpack plugin.
-
E.
Laravel Scout
Laravel Scout is a Laravel package that provides a simple, driver-based full-text search abstraction for Eloquent models, integrating with services like Algolia and Meilisearch.
- F. None of above. chosen
Statements (99)
| Predicate | Object |
|---|---|
| instanceOf |
analytics engine
ⓘ
search engine ⓘ software product ⓘ |
| basedOn | Apache Lucene NERFINISHED ⓘ |
| compatibleWith |
Beats
NERFINISHED
ⓘ
Elastic APM NERFINISHED ⓘ Kibana NERFINISHED ⓘ Logstash NERFINISHED ⓘ |
| deploymentModel |
managed cloud service
ⓘ
self-hosted ⓘ |
| developer | Elastic NV NERFINISHED ⓘ |
| hasCloudService |
Elastic Cloud
NERFINISHED
ⓘ
Elasticsearch Service on Elastic Cloud NERFINISHED ⓘ |
| hasConcept |
analyzer
ⓘ
cluster ⓘ document ⓘ index ⓘ mapping ⓘ node ⓘ query DSL ⓘ replica ⓘ shard ⓘ tokenizer ⓘ |
| hasConfiguration | elasticsearch.yml ⓘ |
| initialReleaseDate | 2010 ⓘ |
| license |
Elastic License
NERFINISHED
ⓘ
Server Side Public License NERFINISHED ⓘ |
| partOf | Elastic Stack NERFINISHED ⓘ |
| previousLicense | Apache License 2.0 NERFINISHED ⓘ |
| programmingLanguage | Java ⓘ |
| supportsClient |
.NET client
ⓘ
Go client ⓘ Java client ⓘ JavaScript client ⓘ PHP client ⓘ Python client ⓘ REST client ⓘ Ruby client ⓘ |
| supportsClusterRole |
coordinating node
ⓘ
data node ⓘ ingest node ⓘ master-eligible node ⓘ |
| supportsDataType |
boolean
ⓘ
date ⓘ geo_point ⓘ geo_shape ⓘ keyword ⓘ nested ⓘ numeric ⓘ object ⓘ text ⓘ |
| supportsFeature |
TLS encryption
ⓘ
aggregations ⓘ cluster coordination ⓘ distributed search ⓘ faceted search ⓘ full-text search ⓘ geospatial search ⓘ horizontal scaling ⓘ index lifecycle management ⓘ ingest pipelines ⓘ machine learning integration ⓘ multi-tenant indices ⓘ near real-time indexing ⓘ real-time search ⓘ replication ⓘ role-based access control ⓘ schema-free JSON documents ⓘ sharding ⓘ snapshot and restore ⓘ structured search ⓘ |
| supportsIndexingMode |
batch indexing
ⓘ
bulk indexing ⓘ streaming indexing ⓘ |
| supportsInterface |
HTTP
NERFINISHED
ⓘ
JSON NERFINISHED ⓘ REST API NERFINISHED ⓘ |
| supportsProtocol |
HTTP
ⓘ
HTTPS ⓘ |
| supportsQueryType |
aggregations query
ⓘ
bool query ⓘ match query ⓘ range query ⓘ term query ⓘ |
| supportsSecurityFeature |
IP filtering
ⓘ
audit logging ⓘ authentication ⓘ authorization ⓘ document-level security ⓘ encryption at rest (via external tools) ⓘ encryption in transit ⓘ field-level security ⓘ |
| useCase |
application search
ⓘ
business intelligence ⓘ log analytics ⓘ metrics analytics ⓘ real-time data exploration ⓘ security analytics ⓘ site search ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Elasticsearch Description of subject: Elasticsearch is a distributed, RESTful search and analytics engine built on Apache Lucene, widely used for full-text search, log analytics, and real-time data exploration.
Referenced by (4)
Full triples — surface form annotated when it differs from this entity's canonical label.