Our results clearly indicate that both DNNs were able to generalize and obtain promising precision results, that are further improved when their scores are averaged.
combining the predictions of a DNN trained over prefixes of sentences enriched with claims, with those by a DNN trained over suffixes of such sentences, results in a pincer-movement like approach, that successfully pinpoints a wide range of CS in a massive unstructured corpus, while using only weak supervision for training.