Knowledge extraction
creation of knowledge from structured and unstructured sources
Knowledge extraction is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing. Although it is methodically similar to information extraction (IE) in natural language processing (NLP) and extract, transform, load (ETL), the main criterion is that the extraction result goes beyond the creation of structured information or the transformation into a relational schema. It requires either the reuse of existing formal knowledge (reusing identifiers or ontologies) or the generation of a schema based on the source data.
The RDB2RDF W3C group was standardizing a language for extraction of resource description frameworks (RDF) from relational databases. Another popular example for knowledge extraction is the transformation of Wikipedia into structured data and also the mapping to existing knowledge (see DBpedia and Freebase).
Overview
After the standardization of knowledge representation languages such as RDF and OWL, much research has been conducted in the area, especially regarding transforming relational databases into RDF, identity resolution, knowledge discovery and ontology learning. The general process uses traditional methods from information extraction and extract, transform, and load (ETL), which transform the data from the sources into structured formats. So understanding how the interact and learn from each other.
The following criteria can be used to categorize approaches in this topic (some of them only account for extraction from relational databases):
Examples
Entity linking
DBpedia Spotlight, OpenCalais, Dandelion dataTXT, the Zemanta API, Extractiv and PoolParty Extractor analyze free text via named-entity recognition and then disambiguates candidates via name resolution and links the found entities to the DBpedia knowledge repository (Dandelion dataTXT demo Archived 2013-11-02 at the Wayback Machine or DBpedia Spotlight web demo or PoolParty Extractor Demo).
Begin with the source’s own compact description: “Knowledge extraction” is creation of knowledge from structured and unstructured sources. The dossier treats that line as a proposition to test through Knowledge, extraction and creation, not as a finished interpretation.
Why this record matters
The phrase “creation of knowledge from structured and unstructured sources” supplies a clear boundary for inquiry. It also exposes the unanswered questions: who defined that boundary, when it became stable and which sources sit outside it.
The citation trail is more important than the brevity of the summary: it shows where individual claims can be examined in context. The source revision retrieved here is dated Aug 20, 2026. The linked authority identifier is Q1582085. None of the 0 selected statements returned an explicit reference. The first chronological checks are 2013.
A concise general-reference account can conceal disagreements about scope, terminology or the weight assigned to individual sources. The source lead contains qualifying language; that uncertainty should survive quotation, summary and reuse. Authority statements aid reconciliation but still require their own references, qualifiers and ranks to be checked.
How to read it
Use the entry as an orientation point, then follow its citations and revision history. Names, dates and institutional relationships should be checked against the original record.
- Subject orientation
- Search vocabulary
- Locating named sources
The closest primary source, responsible institution and strongest cited specialist reference.
Three-step research path
- Establish the record: confirm the title “Knowledge extraction”, its source revision and the description used here.
- Expand the search: follow Knowledge extraction primary sources, Knowledge extraction archive and Knowledge research across catalogues and specialist indexes.
- Test the account: compare the strongest cited source with the responsible institution’s current record and note any disagreement.
Questions for further research
- Which source most directly establishes the central claim about “Knowledge extraction”?
- Which institution is responsible for the underlying evidence?
- Which cited source is closest to the event, object or claim?
Search terms from this dossier
This entry incorporates text from “Knowledge extraction” on English Wikipedia. Contributors are listed in the page history. Text is available under the Creative Commons Attribution-ShareAlike 4.0 License. Selected authority identifiers and statements are retrieved from Wikidata under CC0; their references and qualifiers remain part of the verification path.