How to use the wink-bm25-text-search/sample-data/demo-data-for-wink-bm25.json.forEach function in wink-bm25-text-search

nlp.tokens.stem,
  nlp.tokens.propagateNegations
];
// Contains search query.
var query;

// Step I: Define config
// Only field weights are required in this example.
engine.defineConfig( { fldWeights: { title: 1, body: 2 } } );
// Step II: Define PrepTasks pipe.
// Set up 'default' preparatory tasks i.e. for everything else
engine.definePrepTasks( pipe );

// Step III: Add Docs
// Add documents now...
docs.forEach( function ( doc, i ) {
  // Note, 'i' becomes the unique id for 'doc'
  engine.addDoc( doc, i );
} );

// Step IV: Consolidate
// Consolidate before searching
engine.consolidate();

// All set, start searching!
query = 'not studied law';
// `results` is an array of [ doc-id, score ], sorted by score
var results = engine.search( query );
// Print number of results.
console.log( '%d entries found.', results.length );
// -> 1 entries found.
// results[ 0 ][ 0 ] i.e. the top result is: