addEntityDetails — Add named-entity tags to tokenized documents.

addEntityDetails(documents) adds named-entity metadata to a RunMat tokenizedDocument compatibility object. Use tokenDetails to view the resulting Entity column.

Syntax

updatedDocuments = addEntityDetails(documents)
updatedDocuments = addEntityDetails(documents,Name,Value)

Inputs

NameTypeRequiredDefaultDescription
documentsAnyYestokenizedDocument object.
NameValueAnyVariadicName-value options: RetokenizeMethod, DiscardKnownValues, Model.

Returns

NameTypeDescription
updatedDocumentsAnyUpdated tokenized document object.

Errors

IdentifierWhenMessage
RunMat:addEntityDetails:InvalidInputInput is not a supported tokenizedDocument object or option form.addEntityDetails: invalid input

How addEntityDetails works

  • documents must be a RunMat tokenizedDocument object.
  • addEntityDetails(documents, Name, Value) supports RetokenizeMethod, DiscardKnownValues, and Model name-value pairs.
  • RetokenizeMethod defaults to "entity", which merges simple adjacent entity tokens such as multiword locations. Use "none" to keep existing tokens.
  • DiscardKnownValues defaults to false, so existing known entity details are preserved while missing or empty entries are filled.
  • DiscardKnownValues, true recomputes every stored tag and ignores malformed stored entity details.
  • Model, "auto" selects RunMat's built-in deterministic compatibility tagger. Custom hmmEntityModel inputs remain tracked as broader Text Analytics model infrastructure.
  • addEntityDetails ensures sentence and part-of-speech details exist first, then updates part-of-speech details for recognized entities to "proper-noun".
  • RunMat tags English and German tokens with deterministic compatibility rules for person, location, organization, other, and non-entity.
  • If an existing tokenizedDocument object already carries Japanese or Korean language metadata, RunMat accepts the language and uses conservative token-class-aware fallback tags. Public Japanese/Korean tokenizedDocument construction and MeCab-backed entity models remain tracked.
  • Exact MathWorks statistical entity-model parity remains tracked as broader Text Analytics work.

GPU memory and residency

addEntityDetails updates host tokenizedDocument metadata and has no provider kernel.

Examples

Add Entity Details

documents = tokenizedDocument("Mary uses MATLAB at MathWorks.");
documents = addEntityDetails(documents);
tdetails = tokenDetails(documents)

Expected output:

`tdetails.Entity` contains tags such as `"person"`, `"organization"`, `"other"`, and `"non-entity"`.

Keep Existing Tokens

documents = addEntityDetails(documents, "RetokenizeMethod", "none")

Expected output:

`documents` receives entity details without the entity retokenization pass.

Recompute Entity Details

documents = addEntityDetails(documents, "DiscardKnownValues", true)

Expected output:

`documents` has refreshed entity details.

Using addEntityDetails with coding agents

Open a RunMat example with live inputs, then ask the agent to explain how addEntityDetails changes the result.

Run a small addEntityDetails example, explain the result, then change one input and compare the output.

FAQ

Does addEntityDetails use a full entity model?

No. This compatibility slice uses deterministic English and German rules and records exact MathWorks model parity as remaining Text Analytics work.

Does addEntityDetails execute on the GPU?

No. It updates host tokenizedDocument metadata.

Open-source implementation

Unlike proprietary runtimes, every RunMat function is open-source. Read exactly how addEntityDetails is executed, line by line, in Rust.

About RunMat

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