diff --git a/src/doc-v2.js b/src/doc-v2.js
index 5e3d2be..bc5bf70 100644
--- a/src/doc-v2.js
+++ b/src/doc-v2.js
@@ -459,10 +459,14 @@ var doc = function ( docData, addons ) {
   // eslint-disable-next-line complexity
   contextualVectors = function ( { lemma = true, specificWordVectors = [], similarWordVectors = false, wordVectorsLimit = 0 } = {} ) {
     // Error handling!
+    if ( docData.wordVectors === null )
+      throw Error( 'wink-nlp: word vectors are not loaded: load them winkNLP\'s instantiation time.' );
     if ( !Array.isArray( specificWordVectors ) )
       throw Error( `wink-nlp: expecting a valid Javascript array for similarWordVectos, instead found "${typeof specificWordVectors}".`);
     if ( !Number.isInteger( wordVectorsLimit ) || wordVectorsLimit >= docData.wordVectors.size )
       throw Error( 'wink-nlp: invalid value or type encountered for wordVectorsLimit.' );
+    if ( lemma && !docData.currPipe.pos )
+      throw Error( 'wink-nlp: Can\'t create lemma vectors without pos: add a "pos" to NLP pipe.' );
     // Initialize contextual vectors.
     const cv = Object.create( null );
     // Following properties are constants, therefore can be directly copied.
diff --git a/test/contextual-vectors-specs.js b/test/contextual-vectors-specs.js
index 1581ba3..d5d1b9b 100644
--- a/test/contextual-vectors-specs.js
+++ b/test/contextual-vectors-specs.js
@@ -161,4 +161,18 @@ describe( 'contextual vectors', function () {
     expect( doc1.contextualVectors.bind( null, { specificWordVectors: {} } ) ).to.throw( /^wink-nlp: expecting a valid Javascript/ );
     expect( doc1.contextualVectors.bind( null, { specificWordVectors: 'a' } ) ).to.throw( /^wink-nlp: expecting a valid Javascript/ );
   } );
+
+  it( 'missing word vectors should throw error', function () {
+    const nlpWithNoVW = winkNLP( model );
+    const textNoVW = 'It is';
+    const docNoVW = nlpWithNoVW.readDoc( textNoVW );
+    expect( () => docNoVW.contextualVectors() ).to.throw( /^wink-nlp: word vectors are not loaded/ );
+  } );
+
+  it( 'lemma: true and missing pos in pipe should throw error', function () {
+    const nlpMissingPOS = winkNLP( model, [ 'sbd' ], vectors );
+    const textMissingPOS = 'It is';
+    const docMissingPOS = nlpMissingPOS.readDoc( textMissingPOS );
+    expect( () => docMissingPOS.contextualVectors() ).to.throw( /^wink-nlp: Can\'t create lemma vectors/ );
+  } );
 } );
diff --git a/types/index.d.ts b/types/index.d.ts
index 31fa2cf..62ec5e9 100644
--- a/types/index.d.ts
+++ b/types/index.d.ts
@@ -271,6 +271,13 @@ declare module 'wink-nlp' {
     out<T, U>(itsf: ItsFunction<T>, asf: AsFunction<T, U>): U | T[] | string[];
   }
 
+  export interface Include {
+    lemma?: boolean;
+    specificWordVectors?: string[];
+    similarWordVectors?: boolean;
+    wordVectorsLimit?: number;
+  }
+
   export interface Document {
     entities(): Entities;
     customEntities(): CustomEntities;
@@ -282,7 +289,7 @@ declare module 'wink-nlp' {
     tokens(): Tokens;
     printTokens(): void;
     pipeConfig(): string[];
-    contextualVectors(lemma: boolean, specifcWordVectors: string[], similarWordVectors: boolean, wordVectorsLimit: number): string;
+    contextualVectors(include: Include): string;
   }
 
   export interface CerExample {
@@ -317,6 +324,7 @@ declare module 'wink-nlp' {
     readDoc(text: string): Document;
     // returns number of learned entities
     learnCustomEntities(examples: CustomEntityExample[], config?: CerConfig): number;
+    vectorOf(word: string): number[];
     its: ItsHelpers;
     as: AsHelpers;
   }