True Negatives for Named Entity Recognition
By definition, true negative is non-entity tokens in the text, agreed by gold standard. So;
TN: 5 = {announced, the, release, of}
But, in practice the number of true negative tokens are quite high and this heavily dominates the metrics, and any measure using TN (like accuracy) becomes highly controversial. Instead, preferred better metrics:

Recall: TP/(TP+FN) - coverage in all correct entities, and
Precision: TP/(TP+FP) - how reliable for a positive result
F1 Score (harmonic mean of precision and recall) can be used as a balanced metrics.